diff --git "a/log/train_log" "b/log/train_log"
new file mode 100644--- /dev/null
+++ "b/log/train_log"
@@ -0,0 +1,12239 @@
+# Running on vgni001
+# Started at Mon 28 Nov 15:12:15 CET 2022
+# python3 src/run_speech_recognition_ctc.py --report_to=none --run_name=experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/ --preprocessing_num_workers=5 --model_name_or_path=facebook/wav2vec2-large-960h-lv60-self --dataset_name=experiments/data/uwb_atcc/train --min_duration_in_seconds=0.2 --max_duration_in_seconds=20 --eval_dataset_name=experiments/data/uwb_atcc/test --train_split_name=train --output_dir=experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/ --num_train_epochs=50 --per_device_train_batch_size=24 --per_device_eval_batch_size=12 --gradient_accumulation_steps=1 --learning_rate=1e-4 --weight_decay=0.001 --warmup_steps=1000 --evaluation_strategy=steps --text_column_name=text --audio_column_name=audio --length_column_name=input_length '--chars_to_ignore=, ? . ! \; \: " “ % ‘ ” � — ’ … –' --save_steps=1000 --eval_steps=500 --logging_steps=1000 --layerdrop=0.0 --activation_dropout=0.0 --attention_dropout=0.0 --save_total_limit=1 --feat_proj_dropout=0.05 --mask_time_prob=0.075 --mask_time_length=12 --mask_feature_prob=0.0 --mask_feature_length=12 --gradient_checkpointing --freeze_feature_encoder --fp16 --group_by_length --do_train --do_eval --max_steps 10000 --overwrite_output_dir --freeze_feature_encoder
+11/28/2022 15:12:25 - WARNING - __main__ - Process rank: -1, device: cuda:0, n_gpu: 1distributed training: False, 16-bits training: True
+11/28/2022 15:12:25 - INFO - __main__ - Training/evaluation parameters TrainingArguments(
+_n_gpu=1,
+adafactor=False,
+adam_beta1=0.9,
+adam_beta2=0.999,
+adam_epsilon=1e-08,
+auto_find_batch_size=False,
+bf16=False,
+bf16_full_eval=False,
+data_seed=None,
+dataloader_drop_last=False,
+dataloader_num_workers=0,
+dataloader_pin_memory=True,
+ddp_bucket_cap_mb=None,
+ddp_find_unused_parameters=None,
+ddp_timeout=1800,
+debug=[],
+deepspeed=None,
+disable_tqdm=False,
+do_eval=True,
+do_predict=False,
+do_train=True,
+eval_accumulation_steps=None,
+eval_delay=0,
+eval_steps=500,
+evaluation_strategy=steps,
+fp16=True,
+fp16_backend=auto,
+fp16_full_eval=False,
+fp16_opt_level=O1,
+fsdp=[],
+fsdp_min_num_params=0,
+fsdp_transformer_layer_cls_to_wrap=None,
+full_determinism=False,
+gradient_accumulation_steps=1,
+gradient_checkpointing=True,
+greater_is_better=None,
+group_by_length=True,
+half_precision_backend=auto,
+hub_model_id=None,
+hub_private_repo=False,
+hub_strategy=every_save,
+hub_token=<HUB_TOKEN>,
+ignore_data_skip=False,
+include_inputs_for_metrics=False,
+jit_mode_eval=False,
+label_names=None,
+label_smoothing_factor=0.0,
+learning_rate=0.0001,
+length_column_name=input_length,
+load_best_model_at_end=False,
+local_rank=-1,
+log_level=passive,
+log_level_replica=passive,
+log_on_each_node=True,
+logging_dir=experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/runs/Nov28_15-12-25_vgni001,
+logging_first_step=False,
+logging_nan_inf_filter=True,
+logging_steps=1000,
+logging_strategy=steps,
+lr_scheduler_type=linear,
+max_grad_norm=1.0,
+max_steps=10000,
+metric_for_best_model=None,
+mp_parameters=,
+no_cuda=False,
+num_train_epochs=50.0,
+optim=adamw_hf,
+output_dir=experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/,
+overwrite_output_dir=True,
+past_index=-1,
+per_device_eval_batch_size=12,
+per_device_train_batch_size=24,
+prediction_loss_only=False,
+push_to_hub=False,
+push_to_hub_model_id=None,
+push_to_hub_organization=None,
+push_to_hub_token=<PUSH_TO_HUB_TOKEN>,
+ray_scope=last,
+remove_unused_columns=True,
+report_to=[],
+resume_from_checkpoint=None,
+run_name=experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/,
+save_on_each_node=False,
+save_steps=1000,
+save_strategy=steps,
+save_total_limit=1,
+seed=42,
+sharded_ddp=[],
+skip_memory_metrics=True,
+tf32=None,
+torchdynamo=None,
+tpu_metrics_debug=False,
+tpu_num_cores=None,
+use_ipex=False,
+use_legacy_prediction_loop=False,
+use_mps_device=False,
+warmup_ratio=0.0,
+warmup_steps=1000,
+weight_decay=0.001,
+xpu_backend=None,
+)
+11/28/2022 15:12:25 - WARNING - datasets.builder - Using custom data configuration train-755c6b8b7f9b046c
+Downloading and preparing dataset atc_data_loader/train to /remote/idiap.svm/temp.speech01/jzuluaga/experiments/journal/asr/github/w2v2-air-traffic/.cache/experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc//train/atc_data_loader/train-755c6b8b7f9b046c/0.0.0/f2633cc53c6abe32cddd4152eebde1a4e3c9953e1446e190b8d9a13330cddaa4...
+
Generating train split: 0 examples [00:00, ? examples/s]
Generating train split: 1 examples [00:25, 25.81s/ examples]
Generating train split: 256 examples [00:25, 14.05 examples/s]
Generating train split: 700 examples [00:26, 48.51 examples/s]
Generating train split: 1040 examples [00:26, 85.34 examples/s]
Generating train split: 1536 examples [00:26, 159.93 examples/s]
Generating train split: 2011 examples [00:26, 258.66 examples/s]
Generating train split: 2407 examples [00:26, 368.13 examples/s]
Generating train split: 2816 examples [00:26, 515.49 examples/s]
Generating train split: 3319 examples [00:26, 761.90 examples/s]
Generating train split: 3732 examples [00:26, 998.39 examples/s]
Generating train split: 4133 examples [00:26, 1246.55 examples/s]
Generating train split: 4608 examples [00:27, 1592.25 examples/s]
Generating train split: 5109 examples [00:27, 2059.00 examples/s]
Generating train split: 5520 examples [00:27, 2273.72 examples/s]
Generating train split: 5900 examples [00:27, 2480.44 examples/s]
Generating train split: 6400 examples [00:27, 2871.80 examples/s]
Generating train split: 6885 examples [00:27, 3299.35 examples/s]
Generating train split: 7297 examples [00:27, 3344.26 examples/s]
Generating train split: 7690 examples [00:27, 3397.37 examples/s]
Generating train split: 8192 examples [00:28, 3554.49 examples/s]
Generating train split: 8704 examples [00:28, 3660.94 examples/s]
Generating train split: 9216 examples [00:28, 3807.51 examples/s]
Generating train split: 9728 examples [00:28, 3922.50 examples/s]
Generating train split: 10238 examples [00:28, 4221.47 examples/s]
Generating train split: 10673 examples [00:28, 4114.93 examples/s]
Generating train split: 11093 examples [00:28, 3872.86 examples/s]
Dataset atc_data_loader downloaded and prepared to /remote/idiap.svm/temp.speech01/jzuluaga/experiments/journal/asr/github/w2v2-air-traffic/.cache/experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc//train/atc_data_loader/train-755c6b8b7f9b046c/0.0.0/f2633cc53c6abe32cddd4152eebde1a4e3c9953e1446e190b8d9a13330cddaa4. Subsequent calls will reuse this data.
+11/28/2022 15:12:55 - WARNING - datasets.builder - Using custom data configuration test-085e5dd7a4b8bb1c
+Downloading and preparing dataset atc_data_loader/test to /remote/idiap.svm/temp.speech01/jzuluaga/experiments/journal/asr/github/w2v2-air-traffic/.cache/experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc//test/atc_data_loader/test-085e5dd7a4b8bb1c/0.0.0/f2633cc53c6abe32cddd4152eebde1a4e3c9953e1446e190b8d9a13330cddaa4...
+
Generating test split: 0 examples [00:00, ? examples/s]
Generating test split: 1 examples [00:05, 5.73s/ examples]
Generating test split: 285 examples [00:05, 69.22 examples/s]
Generating test split: 655 examples [00:05, 191.09 examples/s]
Generating test split: 1024 examples [00:06, 348.81 examples/s]
Generating test split: 1536 examples [00:06, 634.68 examples/s]
Generating test split: 2048 examples [00:06, 979.63 examples/s]
Generating test split: 2506 examples [00:06, 1342.98 examples/s]
loading configuration file config.json from cache at /idiap/temp/jzuluaga/cache/huggingface/models--facebook--wav2vec2-large-960h-lv60-self/snapshots/54074b1c16f4de6a5ad59affb4caa8f2ea03a119/config.json
+Model config Wav2Vec2Config {
+ "_name_or_path": "facebook/wav2vec2-large-960h-lv60-self",
+ "activation_dropout": 0.1,
+ "adapter_kernel_size": 3,
+ "adapter_stride": 2,
+ "add_adapter": false,
+ "apply_spec_augment": true,
+ "architectures": [
+ "Wav2Vec2ForCTC"
+ ],
+ "attention_dropout": 0.1,
+ "bos_token_id": 1,
+ "classifier_proj_size": 256,
+ "codevector_dim": 256,
+ "contrastive_logits_temperature": 0.1,
+ "conv_bias": true,
+ "conv_dim": [
+ 512,
+ 512,
+ 512,
+ 512,
+ 512,
+ 512,
+ 512
+ ],
+ "conv_kernel": [
+ 10,
+ 3,
+ 3,
+ 3,
+ 3,
+ 2,
+ 2
+ ],
+ "conv_stride": [
+ 5,
+ 2,
+ 2,
+ 2,
+ 2,
+ 2,
+ 2
+ ],
+ "ctc_loss_reduction": "sum",
+ "ctc_zero_infinity": false,
+ "diversity_loss_weight": 0.1,
+ "do_stable_layer_norm": true,
+ "eos_token_id": 2,
+ "feat_extract_activation": "gelu",
+ "feat_extract_dropout": 0.0,
+ "feat_extract_norm": "layer",
+ "feat_proj_dropout": 0.1,
+ "feat_quantizer_dropout": 0.0,
+ "final_dropout": 0.1,
+ "gradient_checkpointing": false,
+ "hidden_act": "gelu",
+ "hidden_dropout": 0.1,
+ "hidden_dropout_prob": 0.1,
+ "hidden_size": 1024,
+ "initializer_range": 0.02,
+ "intermediate_size": 4096,
+ "layer_norm_eps": 1e-05,
+ "layerdrop": 0.1,
+ "mask_feature_length": 10,
+ "mask_feature_min_masks": 0,
+ "mask_feature_prob": 0.0,
+ "mask_time_length": 10,
+ "mask_time_min_masks": 2,
+ "mask_time_prob": 0.05,
+ "model_type": "wav2vec2",
+ "num_adapter_layers": 3,
+ "num_attention_heads": 16,
+ "num_codevector_groups": 2,
+ "num_codevectors_per_group": 320,
+ "num_conv_pos_embedding_groups": 16,
+ "num_conv_pos_embeddings": 128,
+ "num_feat_extract_layers": 7,
+ "num_hidden_layers": 24,
+ "num_negatives": 100,
+ "output_hidden_size": 1024,
+ "pad_token_id": 0,
+ "proj_codevector_dim": 256,
+ "tdnn_dilation": [
+ 1,
+ 2,
+ 3,
+ 1,
+ 1
+ ],
+ "tdnn_dim": [
+ 512,
+ 512,
+ 512,
+ 512,
+ 1500
+ ],
+ "tdnn_kernel": [
+ 5,
+ 3,
+ 3,
+ 1,
+ 1
+ ],
+ "transformers_version": "4.24.0",
+ "use_weighted_layer_sum": false,
+ "vocab_size": 32,
+ "xvector_output_dim": 512
+}
+
+Dataset atc_data_loader downloaded and prepared to /remote/idiap.svm/temp.speech01/jzuluaga/experiments/journal/asr/github/w2v2-air-traffic/.cache/experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc//test/atc_data_loader/test-085e5dd7a4b8bb1c/0.0.0/f2633cc53c6abe32cddd4152eebde1a4e3c9953e1446e190b8d9a13330cddaa4. Subsequent calls will reuse this data.
+
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+
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+loading file vocab.json
+loading file tokenizer_config.json
+loading file added_tokens.json
+loading file special_tokens_map.json
+Adding <s> to the vocabulary
+Adding </s> to the vocabulary
+Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
+loading configuration file preprocessor_config.json from cache at /idiap/temp/jzuluaga/cache/huggingface/models--facebook--wav2vec2-large-960h-lv60-self/snapshots/54074b1c16f4de6a5ad59affb4caa8f2ea03a119/preprocessor_config.json
+loading configuration file config.json from cache at /idiap/temp/jzuluaga/cache/huggingface/models--facebook--wav2vec2-large-960h-lv60-self/snapshots/54074b1c16f4de6a5ad59affb4caa8f2ea03a119/config.json
+Model config Wav2Vec2Config {
+ "_name_or_path": "facebook/wav2vec2-large-960h-lv60-self",
+ "activation_dropout": 0.1,
+ "adapter_kernel_size": 3,
+ "adapter_stride": 2,
+ "add_adapter": false,
+ "apply_spec_augment": true,
+ "architectures": [
+ "Wav2Vec2ForCTC"
+ ],
+ "attention_dropout": 0.1,
+ "bos_token_id": 1,
+ "classifier_proj_size": 256,
+ "codevector_dim": 256,
+ "contrastive_logits_temperature": 0.1,
+ "conv_bias": true,
+ "conv_dim": [
+ 512,
+ 512,
+ 512,
+ 512,
+ 512,
+ 512,
+ 512
+ ],
+ "conv_kernel": [
+ 10,
+ 3,
+ 3,
+ 3,
+ 3,
+ 2,
+ 2
+ ],
+ "conv_stride": [
+ 5,
+ 2,
+ 2,
+ 2,
+ 2,
+ 2,
+ 2
+ ],
+ "ctc_loss_reduction": "sum",
+ "ctc_zero_infinity": false,
+ "diversity_loss_weight": 0.1,
+ "do_stable_layer_norm": true,
+ "eos_token_id": 2,
+ "feat_extract_activation": "gelu",
+ "feat_extract_dropout": 0.0,
+ "feat_extract_norm": "layer",
+ "feat_proj_dropout": 0.1,
+ "feat_quantizer_dropout": 0.0,
+ "final_dropout": 0.1,
+ "gradient_checkpointing": false,
+ "hidden_act": "gelu",
+ "hidden_dropout": 0.1,
+ "hidden_dropout_prob": 0.1,
+ "hidden_size": 1024,
+ "initializer_range": 0.02,
+ "intermediate_size": 4096,
+ "layer_norm_eps": 1e-05,
+ "layerdrop": 0.1,
+ "mask_feature_length": 10,
+ "mask_feature_min_masks": 0,
+ "mask_feature_prob": 0.0,
+ "mask_time_length": 10,
+ "mask_time_min_masks": 2,
+ "mask_time_prob": 0.05,
+ "model_type": "wav2vec2",
+ "num_adapter_layers": 3,
+ "num_attention_heads": 16,
+ "num_codevector_groups": 2,
+ "num_codevectors_per_group": 320,
+ "num_conv_pos_embedding_groups": 16,
+ "num_conv_pos_embeddings": 128,
+ "num_feat_extract_layers": 7,
+ "num_hidden_layers": 24,
+ "num_negatives": 100,
+ "output_hidden_size": 1024,
+ "pad_token_id": 0,
+ "proj_codevector_dim": 256,
+ "tdnn_dilation": [
+ 1,
+ 2,
+ 3,
+ 1,
+ 1
+ ],
+ "tdnn_dim": [
+ 512,
+ 512,
+ 512,
+ 512,
+ 1500
+ ],
+ "tdnn_kernel": [
+ 5,
+ 3,
+ 3,
+ 1,
+ 1
+ ],
+ "transformers_version": "4.24.0",
+ "use_weighted_layer_sum": false,
+ "vocab_size": 32,
+ "xvector_output_dim": 512
+}
+
+Feature extractor Wav2Vec2FeatureExtractor {
+ "do_normalize": true,
+ "feature_extractor_type": "Wav2Vec2FeatureExtractor",
+ "feature_size": 1,
+ "padding_side": "right",
+ "padding_value": 0.0,
+ "return_attention_mask": true,
+ "sampling_rate": 16000
+}
+
+loading weights file pytorch_model.bin from cache at /idiap/temp/jzuluaga/cache/huggingface/models--facebook--wav2vec2-large-960h-lv60-self/snapshots/54074b1c16f4de6a5ad59affb4caa8f2ea03a119/pytorch_model.bin
+All model checkpoint weights were used when initializing Wav2Vec2ForCTC.
+
+Some weights of Wav2Vec2ForCTC were not initialized from the model checkpoint at facebook/wav2vec2-large-960h-lv60-self and are newly initialized: ['wav2vec2.masked_spec_embed']
+You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.
+Some weights of Wav2Vec2ForCTC were not initialized from the model checkpoint at facebook/wav2vec2-large-960h-lv60-self and are newly initialized because the shapes did not match:
+- lm_head.weight: found shape torch.Size([32, 1024]) in the checkpoint and torch.Size([31, 1024]) in the model instantiated
+- lm_head.bias: found shape torch.Size([32]) in the checkpoint and torch.Size([31]) in the model instantiated
+You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.
+
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+
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+
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+
+
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+
+
+
+
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+ array = librosa.resample(array, sampling_rate, self.sampling_rate, res_type="kaiser_best")
+/idiap/user/jzuluaga/miniconda3/envs/w2v2/lib/python3.10/site-packages/datasets/features/audio.py:279: FutureWarning: Pass orig_sr=8000, target_sr=16000 as keyword args. From version 0.10 passing these as positional arguments will result in an error
+ array = librosa.resample(array, sampling_rate, self.sampling_rate, res_type="kaiser_best")
+/idiap/user/jzuluaga/miniconda3/envs/w2v2/lib/python3.10/site-packages/datasets/features/audio.py:279: FutureWarning: Pass orig_sr=8000, target_sr=16000 as keyword args. From version 0.10 passing these as positional arguments will result in an error
+ array = librosa.resample(array, sampling_rate, self.sampling_rate, res_type="kaiser_best")
+/idiap/user/jzuluaga/miniconda3/envs/w2v2/lib/python3.10/site-packages/datasets/features/audio.py:279: FutureWarning: Pass orig_sr=8000, target_sr=16000 as keyword args. From version 0.10 passing these as positional arguments will result in an error
+ array = librosa.resample(array, sampling_rate, self.sampling_rate, res_type="kaiser_best")
+/idiap/user/jzuluaga/miniconda3/envs/w2v2/lib/python3.10/site-packages/datasets/features/audio.py:279: FutureWarning: Pass orig_sr=8000, target_sr=16000 as keyword args. From version 0.10 passing these as positional arguments will result in an error
+ array = librosa.resample(array, sampling_rate, self.sampling_rate, res_type="kaiser_best")
+
+
+
+
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+ array = librosa.resample(array, sampling_rate, self.sampling_rate, res_type="kaiser_best")
+
+
preprocess datasets #1: 0%| | 1/2258 [00:02<1:39:36, 2.65s/ex][A/idiap/user/jzuluaga/miniconda3/envs/w2v2/lib/python3.10/site-packages/datasets/features/audio.py:279: FutureWarning: Pass orig_sr=8000, target_sr=16000 as keyword args. From version 0.10 passing these as positional arguments will result in an error
+ array = librosa.resample(array, sampling_rate, self.sampling_rate, res_type="kaiser_best")
+
+
+
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preprocess datasets #0: 0%| | 1/2259 [00:02<1:40:23, 2.67s/ex]/idiap/user/jzuluaga/miniconda3/envs/w2v2/lib/python3.10/site-packages/datasets/features/audio.py:279: FutureWarning: Pass orig_sr=8000, target_sr=16000 as keyword args. From version 0.10 passing these as positional arguments will result in an error
+ array = librosa.resample(array, sampling_rate, self.sampling_rate, res_type="kaiser_best")
+/idiap/user/jzuluaga/miniconda3/envs/w2v2/lib/python3.10/site-packages/datasets/features/audio.py:279: FutureWarning: Pass orig_sr=8000, target_sr=16000 as keyword args. From version 0.10 passing these as positional arguments will result in an error
+ array = librosa.resample(array, sampling_rate, self.sampling_rate, res_type="kaiser_best")
+
+
+
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preprocess datasets #0: 8%|▊ | 186/2259 [00:08<01:13, 28.38ex/s]
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preprocess datasets #0: 79%|███████▉ | 1781/2259 [01:00<00:15, 31.18ex/s]
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preprocess datasets #0: 79%|███████▉ | 1785/2259 [01:00<00:16, 29.02ex/s]
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preprocess datasets #0: 79%|███████▉ | 1789/2259 [01:00<00:15, 29.45ex/s]
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preprocess datasets #0: 79%|███████▉ | 1794/2259 [01:00<00:14, 31.53ex/s]
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preprocess datasets #0: 80%|███████▉ | 1798/2259 [01:00<00:15, 30.47ex/s]
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preprocess datasets #0: 80%|███████▉ | 1802/2259 [01:00<00:14, 32.38ex/s]
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preprocess datasets #1: 78%|███████▊ | 1770/2258 [01:01<00:16, 28.80ex/s][A
preprocess datasets #0: 80%|███████▉ | 1806/2259 [01:01<00:13, 33.06ex/s]
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preprocess datasets #2: 81%|████████▏ | 1838/2258 [01:01<00:11, 36.06ex/s][A[A
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preprocess datasets #3: 83%|████████▎ | 1881/2258 [01:01<00:10, 34.54ex/s][A[A[A
preprocess datasets #0: 80%|████████ | 1811/2259 [01:01<00:12, 35.54ex/s]
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preprocess datasets #2: 82%|████████▏ | 1842/2258 [01:01<00:12, 32.37ex/s][A[A
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preprocess datasets #1: 79%|███████▊ | 1778/2258 [01:01<00:15, 31.88ex/s][A
preprocess datasets #0: 80%|████████ | 1818/2259 [01:01<00:10, 42.87ex/s]
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preprocess datasets #3: 83%|████████▎ | 1885/2258 [01:01<00:11, 31.36ex/s][A[A[A
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preprocess datasets #2: 82%|████████▏ | 1846/2258 [01:01<00:12, 32.14ex/s][A[A
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preprocess datasets #1: 79%|███████▉ | 1783/2258 [01:01<00:13, 34.70ex/s][A
preprocess datasets #0: 81%|████████ | 1823/2259 [01:01<00:10, 43.28ex/s]
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preprocess datasets #3: 84%|████████▎ | 1889/2258 [01:01<00:11, 32.34ex/s][A[A[A
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preprocess datasets #2: 82%|████████▏ | 1850/2258 [01:01<00:12, 33.01ex/s][A[A
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preprocess datasets #1: 79%|███████▉ | 1789/2258 [01:01<00:12, 38.20ex/s][A
preprocess datasets #0: 81%|████████ | 1829/2259 [01:01<00:09, 44.87ex/s]
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preprocess datasets #4: 85%|████████▌ | 1929/2258 [01:01<00:11, 29.16ex/s][A[A[A[A
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preprocess datasets #2: 82%|████████▏ | 1854/2258 [01:01<00:12, 32.28ex/s][A[A
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preprocess datasets #3: 84%|████████▍ | 1893/2258 [01:01<00:12, 29.58ex/s][A[A[A
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preprocess datasets #1: 79%|███████▉ | 1794/2258 [01:01<00:11, 40.51ex/s][A
preprocess datasets #0: 81%|████████ | 1834/2259 [01:01<00:10, 41.08ex/s]
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preprocess datasets #4: 86%|████████▌ | 1933/2258 [01:01<00:10, 31.29ex/s][A[A[A[A
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preprocess datasets #2: 82%|████████▏ | 1858/2258 [01:01<00:12, 33.06ex/s][A[A
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preprocess datasets #1: 80%|███████▉ | 1799/2258 [01:01<00:10, 42.27ex/s][A
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preprocess datasets #3: 84%|████████▍ | 1897/2258 [01:01<00:11, 31.09ex/s][A[A[A
preprocess datasets #0: 81%|████████▏ | 1839/2259 [01:01<00:10, 39.94ex/s]
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preprocess datasets #2: 82%|████████▏ | 1862/2258 [01:01<00:11, 34.56ex/s][A[A
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preprocess datasets #4: 86%|████████▌ | 1937/2258 [01:01<00:10, 29.42ex/s][A[A[A[A
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preprocess datasets #1: 80%|███████▉ | 1805/2258 [01:01<00:10, 43.88ex/s][A
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preprocess datasets #3: 84%|████████▍ | 1902/2258 [01:01<00:11, 30.85ex/s][A[A[A
preprocess datasets #0: 82%|████████▏ | 1844/2259 [01:01<00:10, 39.92ex/s]
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preprocess datasets #4: 86%|████████▌ | 1941/2258 [01:01<00:10, 31.56ex/s][A[A[A[A
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preprocess datasets #2: 83%|████████▎ | 1867/2258 [01:01<00:10, 35.91ex/s][A[A
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preprocess datasets #3: 84%|████████▍ | 1907/2258 [01:01<00:10, 34.61ex/s][A[A[A
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preprocess datasets #1: 80%|████████ | 1811/2258 [01:01<00:10, 42.17ex/s][A
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preprocess datasets #2: 83%|████████▎ | 1871/2258 [01:02<00:10, 36.32ex/s][A[A
preprocess datasets #0: 82%|████████▏ | 1849/2259 [01:02<00:10, 39.82ex/s]
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preprocess datasets #4: 86%|████████▌ | 1945/2258 [01:02<00:10, 30.62ex/s][A[A[A[A
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preprocess datasets #3: 85%|████████▍ | 1911/2258 [01:02<00:09, 35.90ex/s][A[A[A
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preprocess datasets #1: 80%|████████ | 1816/2258 [01:02<00:10, 43.28ex/s][A
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preprocess datasets #2: 83%|████████▎ | 1875/2258 [01:02<00:10, 36.99ex/s][A[A
preprocess datasets #0: 82%|████████▏ | 1856/2259 [01:02<00:08, 45.27ex/s]
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preprocess datasets #4: 86%|████████▋ | 1951/2258 [01:02<00:08, 34.62ex/s][A[A[A[A
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preprocess datasets #3: 85%|████████▍ | 1916/2258 [01:02<00:09, 36.69ex/s][A[A[A
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preprocess datasets #1: 81%|████████ | 1823/2258 [01:02<00:09, 46.53ex/s][A
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preprocess datasets #2: 83%|████████▎ | 1881/2258 [01:02<00:09, 39.88ex/s][A[A
preprocess datasets #0: 82%|████████▏ | 1861/2259 [01:02<00:09, 43.49ex/s]
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preprocess datasets #4: 87%|████████▋ | 1955/2258 [01:02<00:09, 32.83ex/s][A[A[A[A
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preprocess datasets #3: 85%|████████▌ | 1921/2258 [01:02<00:09, 37.14ex/s][A[A[A
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preprocess datasets #1: 81%|████████ | 1828/2258 [01:02<00:09, 43.32ex/s][A
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preprocess datasets #2: 83%|████████▎ | 1885/2258 [01:02<00:09, 39.89ex/s][A[A
preprocess datasets #0: 83%|████████▎ | 1867/2259 [01:02<00:08, 46.55ex/s]
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preprocess datasets #3: 85%|████████▌ | 1925/2258 [01:02<00:09, 36.83ex/s][A[A[A
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preprocess datasets #4: 87%|████████▋ | 1959/2258 [01:02<00:09, 31.60ex/s][A[A[A[A
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preprocess datasets #1: 81%|████████ | 1833/2258 [01:02<00:09, 43.24ex/s][A
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preprocess datasets #2: 84%|████████▎ | 1890/2258 [01:02<00:08, 42.10ex/s][A[A
preprocess datasets #0: 83%|████████▎ | 1872/2259 [01:02<00:08, 46.05ex/s]
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preprocess datasets #3: 85%|████████▌ | 1929/2258 [01:02<00:09, 34.49ex/s][A[A[A
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preprocess datasets #1: 81%|████████▏ | 1838/2258 [01:02<00:09, 42.40ex/s][A
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preprocess datasets #4: 87%|████████▋ | 1963/2258 [01:02<00:09, 30.96ex/s][A[A[A[A
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preprocess datasets #2: 84%|████████▍ | 1895/2258 [01:02<00:09, 36.59ex/s][A[A
preprocess datasets #0: 83%|████████▎ | 1877/2259 [01:02<00:09, 40.77ex/s]
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preprocess datasets #3: 86%|████████▌ | 1933/2258 [01:02<00:09, 35.26ex/s][A[A[A
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preprocess datasets #4: 87%|████████▋ | 1967/2258 [01:02<00:09, 30.44ex/s][A[A[A[A
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preprocess datasets #2: 84%|████████▍ | 1899/2258 [01:02<00:10, 34.51ex/s][A[A
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preprocess datasets #3: 86%|████████▌ | 1937/2258 [01:02<00:08, 35.87ex/s][A[A[A
preprocess datasets #0: 83%|████████▎ | 1882/2259 [01:02<00:09, 38.07ex/s]
+
preprocess datasets #1: 82%|████████▏ | 1847/2258 [01:02<00:11, 36.47ex/s][A
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preprocess datasets #4: 87%|████████▋ | 1971/2258 [01:02<00:09, 29.61ex/s][A[A[A[A
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preprocess datasets #2: 84%|████████▍ | 1903/2258 [01:02<00:10, 34.54ex/s][A[A
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preprocess datasets #3: 86%|████████▌ | 1942/2258 [01:02<00:08, 39.03ex/s][A[A[A
preprocess datasets #0: 83%|████████▎ | 1886/2259 [01:02<00:09, 37.51ex/s]
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preprocess datasets #4: 87%|████████▋ | 1974/2258 [01:02<00:09, 28.90ex/s][A[A[A[A
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preprocess datasets #1: 82%|████████▏ | 1851/2258 [01:03<00:11, 35.08ex/s][A
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preprocess datasets #3: 86%|████████▌ | 1946/2258 [01:03<00:08, 38.12ex/s][A[A[A
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preprocess datasets #2: 84%|████████▍ | 1907/2258 [01:03<00:10, 34.40ex/s][A[A
preprocess datasets #0: 84%|████████▎ | 1891/2259 [01:03<00:09, 39.96ex/s]
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preprocess datasets #4: 88%|████████▊ | 1979/2258 [01:03<00:08, 32.88ex/s][A[A[A[A
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preprocess datasets #1: 82%|████████▏ | 1855/2258 [01:03<00:11, 35.14ex/s][A
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preprocess datasets #2: 85%|████████▍ | 1911/2258 [01:03<00:10, 33.16ex/s][A[A
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preprocess datasets #3: 86%|████████▋ | 1950/2258 [01:03<00:08, 34.39ex/s][A[A[A
preprocess datasets #0: 84%|████████▍ | 1896/2259 [01:03<00:09, 39.59ex/s]
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preprocess datasets #4: 88%|████████▊ | 1983/2258 [01:03<00:08, 33.59ex/s][A[A[A[A
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preprocess datasets #2: 85%|████████▍ | 1915/2258 [01:03<00:10, 34.18ex/s][A[A
preprocess datasets #0: 84%|████████▍ | 1901/2259 [01:03<00:09, 35.84ex/s]
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preprocess datasets #4: 88%|████████▊ | 1987/2258 [01:03<00:07, 33.95ex/s][A[A[A[A
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preprocess datasets #3: 87%|████████▋ | 1954/2258 [01:03<00:10, 28.89ex/s][A[A[A
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preprocess datasets #2: 85%|████████▍ | 1919/2258 [01:03<00:10, 33.49ex/s][A[A
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preprocess datasets #1: 83%|████████▎ | 1863/2258 [01:03<00:12, 30.71ex/s][A
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preprocess datasets #4: 88%|████████▊ | 1992/2258 [01:03<00:07, 36.44ex/s][A[A[A[A
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preprocess datasets #3: 87%|████████▋ | 1959/2258 [01:03<00:09, 31.10ex/s][A[A[A
preprocess datasets #0: 84%|████████▍ | 1905/2259 [01:03<00:10, 32.30ex/s]
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preprocess datasets #2: 85%|████████▌ | 1923/2258 [01:03<00:09, 33.77ex/s][A[A
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preprocess datasets #1: 83%|████████▎ | 1867/2258 [01:03<00:12, 32.25ex/s][A
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preprocess datasets #4: 88%|████████▊ | 1997/2258 [01:03<00:07, 37.03ex/s][A[A[A[A
preprocess datasets #0: 85%|████████▍ | 1909/2259 [01:03<00:10, 33.19ex/s]
+
preprocess datasets #1: 83%|████████▎ | 1871/2258 [01:03<00:11, 32.99ex/s][A
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preprocess datasets #2: 85%|████████▌ | 1927/2258 [01:03<00:10, 31.93ex/s][A[A
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preprocess datasets #3: 87%|████████▋ | 1963/2258 [01:03<00:10, 27.79ex/s][A[A[A
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preprocess datasets #1: 83%|████████▎ | 1875/2258 [01:03<00:11, 33.52ex/s][A
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preprocess datasets #2: 86%|████████▌ | 1931/2258 [01:03<00:10, 32.34ex/s][A[A
preprocess datasets #0: 85%|████████▍ | 1913/2259 [01:03<00:11, 30.63ex/s]
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preprocess datasets #3: 87%|████████▋ | 1967/2258 [01:03<00:10, 28.46ex/s][A[A[A
preprocess datasets #0: 85%|████████▍ | 1917/2259 [01:03<00:10, 31.42ex/s]
+
preprocess datasets #1: 83%|████████▎ | 1879/2258 [01:03<00:12, 30.89ex/s][A
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preprocess datasets #2: 86%|████████▌ | 1935/2258 [01:03<00:11, 29.20ex/s][A[A
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preprocess datasets #3: 87%|████████▋ | 1971/2258 [01:03<00:10, 28.42ex/s][A[A[A
preprocess datasets #0: 85%|████████▌ | 1921/2259 [01:04<00:10, 33.25ex/s]
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preprocess datasets #2: 86%|████████▌ | 1939/2258 [01:04<00:10, 31.47ex/s][A[A
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preprocess datasets #1: 83%|████████▎ | 1883/2258 [01:04<00:12, 29.05ex/s][A
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preprocess datasets #3: 87%|████████▋ | 1974/2258 [01:04<00:10, 26.84ex/s][A[A[A
preprocess datasets #0: 85%|████████▌ | 1925/2259 [01:04<00:09, 33.56ex/s]
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preprocess datasets #4: 89%|████████▊ | 2001/2258 [01:04<00:15, 16.76ex/s][A[A[A[A
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preprocess datasets #3: 88%|████████▊ | 1977/2258 [01:04<00:10, 27.51ex/s][A[A[A
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preprocess datasets #1: 84%|████████▎ | 1886/2258 [01:04<00:14, 25.43ex/s][A
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preprocess datasets #2: 86%|████████▌ | 1943/2258 [01:04<00:11, 27.41ex/s][A[A
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preprocess datasets #4: 89%|████████▉ | 2004/2258 [01:04<00:13, 18.50ex/s][A[A[A[A
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preprocess datasets #3: 88%|████████▊ | 1982/2258 [01:04<00:08, 32.36ex/s][A[A[A
preprocess datasets #0: 85%|████████▌ | 1929/2259 [01:04<00:11, 27.72ex/s]
+
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preprocess datasets #2: 86%|████████▌ | 1946/2258 [01:04<00:11, 27.60ex/s][A[A
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preprocess datasets #1: 84%|████████▎ | 1889/2258 [01:04<00:14, 25.84ex/s][A
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preprocess datasets #4: 89%|████████▉ | 2007/2258 [01:04<00:12, 20.19ex/s][A[A[A[A
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preprocess datasets #3: 88%|████████▊ | 1987/2258 [01:04<00:07, 35.46ex/s][A[A[A
preprocess datasets #0: 86%|████████▌ | 1933/2259 [01:04<00:10, 30.44ex/s]
+
preprocess datasets #1: 84%|████████▍ | 1892/2258 [01:04<00:14, 25.38ex/s][A
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preprocess datasets #2: 86%|████████▋ | 1949/2258 [01:04<00:12, 24.19ex/s][A[A
preprocess datasets #0: 86%|████████▌ | 1939/2259 [01:04<00:08, 37.25ex/s]
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preprocess datasets #3: 88%|████████▊ | 1992/2258 [01:04<00:06, 38.44ex/s][A[A[A
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preprocess datasets #4: 89%|████████▉ | 2011/2258 [01:04<00:10, 22.61ex/s][A[A[A[A
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preprocess datasets #1: 84%|████████▍ | 1896/2258 [01:04<00:14, 25.79ex/s][A
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preprocess datasets #2: 86%|████████▋ | 1953/2258 [01:04<00:11, 26.88ex/s][A[A
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preprocess datasets #3: 88%|████████▊ | 1998/2258 [01:04<00:06, 41.18ex/s][A[A[A
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preprocess datasets #4: 89%|████████▉ | 2014/2258 [01:04<00:10, 23.00ex/s][A[A[A[A
preprocess datasets #0: 86%|████████▌ | 1944/2259 [01:04<00:09, 34.24ex/s]
+
preprocess datasets #1: 84%|████████▍ | 1900/2258 [01:04<00:13, 27.00ex/s][A
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preprocess datasets #4: 89%|████████▉ | 2017/2258 [01:04<00:09, 24.46ex/s][A[A[A[A
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preprocess datasets #2: 87%|████████▋ | 1959/2258 [01:04<00:09, 31.13ex/s][A[A
preprocess datasets #0: 86%|████████▌ | 1948/2259 [01:04<00:10, 30.71ex/s]
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preprocess datasets #4: 90%|████████▉ | 2021/2258 [01:04<00:09, 25.66ex/s][A[A[A[A
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preprocess datasets #1: 84%|████████▍ | 1903/2258 [01:04<00:15, 22.25ex/s][A
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preprocess datasets #2: 87%|████████▋ | 1963/2258 [01:04<00:10, 27.75ex/s][A[A
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preprocess datasets #4: 90%|████████▉ | 2026/2258 [01:04<00:07, 30.40ex/s][A[A[A[A
preprocess datasets #0: 86%|████████▋ | 1952/2259 [01:05<00:10, 28.41ex/s]
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preprocess datasets #2: 87%|████████▋ | 1967/2258 [01:05<00:09, 30.01ex/s][A[A
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preprocess datasets #1: 84%|████████▍ | 1908/2258 [01:05<00:12, 27.57ex/s][A
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preprocess datasets #4: 90%|████████▉ | 2030/2258 [01:05<00:07, 32.55ex/s][A[A[A[A
preprocess datasets #0: 87%|████████▋ | 1956/2259 [01:05<00:10, 29.48ex/s]
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preprocess datasets #2: 87%|████████▋ | 1972/2258 [01:05<00:08, 33.30ex/s][A[A
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preprocess datasets #1: 85%|████████▍ | 1912/2258 [01:05<00:12, 28.37ex/s][A
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preprocess datasets #3: 89%|████████▊ | 2003/2258 [01:05<00:13, 19.52ex/s][A[A[A
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preprocess datasets #4: 90%|█████████ | 2036/2258 [01:05<00:05, 37.49ex/s][A[A[A[A
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preprocess datasets #2: 88%|████████▊ | 1976/2258 [01:05<00:08, 33.86ex/s][A[A
preprocess datasets #0: 87%|████████▋ | 1960/2259 [01:05<00:10, 27.73ex/s]
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preprocess datasets #4: 90%|█████████ | 2042/2258 [01:05<00:05, 42.53ex/s][A[A[A[A
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preprocess datasets #1: 85%|████████▍ | 1916/2258 [01:05<00:12, 27.69ex/s][A
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preprocess datasets #2: 88%|████████▊ | 1980/2258 [01:05<00:08, 34.42ex/s][A[A
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preprocess datasets #3: 89%|████████▉ | 2007/2258 [01:05<00:13, 19.09ex/s][A[A[A
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preprocess datasets #4: 91%|█████████ | 2047/2258 [01:05<00:04, 43.55ex/s][A[A[A[A
preprocess datasets #0: 87%|████████▋ | 1963/2259 [01:05<00:11, 25.35ex/s]
+
preprocess datasets #1: 85%|████████▍ | 1919/2258 [01:05<00:13, 26.07ex/s][A
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preprocess datasets #2: 88%|████████▊ | 1985/2258 [01:05<00:07, 38.25ex/s][A[A
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preprocess datasets #4: 91%|█████████ | 2052/2258 [01:05<00:04, 42.45ex/s][A[A[A[A
preprocess datasets #0: 87%|████████▋ | 1967/2259 [01:05<00:10, 27.22ex/s]
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preprocess datasets #3: 89%|████████▉ | 2010/2258 [01:05<00:12, 19.18ex/s][A[A[A
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preprocess datasets #2: 88%|████████▊ | 1990/2258 [01:05<00:06, 39.65ex/s][A[A
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preprocess datasets #1: 85%|████████▌ | 1923/2258 [01:05<00:12, 26.76ex/s][A
preprocess datasets #0: 87%|████████▋ | 1972/2259 [01:05<00:08, 32.48ex/s]
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preprocess datasets #4: 91%|█████████ | 2057/2258 [01:05<00:04, 42.10ex/s][A[A[A[A
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preprocess datasets #3: 89%|████████▉ | 2013/2258 [01:05<00:11, 20.62ex/s][A[A[A
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preprocess datasets #1: 85%|████████▌ | 1926/2258 [01:05<00:12, 26.57ex/s][A
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preprocess datasets #2: 88%|████████▊ | 1995/2258 [01:05<00:07, 35.69ex/s][A[A
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preprocess datasets #4: 91%|█████████▏| 2062/2258 [01:05<00:04, 41.78ex/s][A[A[A[A
preprocess datasets #0: 87%|████████▋ | 1976/2259 [01:05<00:09, 29.38ex/s]
+
preprocess datasets #1: 85%|████████▌ | 1929/2258 [01:05<00:13, 25.28ex/s][A
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preprocess datasets #3: 89%|████████▉ | 2016/2258 [01:05<00:12, 19.64ex/s][A[A[A
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preprocess datasets #4: 92%|█████████▏| 2067/2258 [01:05<00:04, 38.22ex/s][A[A[A[A
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preprocess datasets #1: 86%|████████▌ | 1932/2258 [01:06<00:13, 24.73ex/s][A
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preprocess datasets #3: 89%|████████▉ | 2020/2258 [01:05<00:10, 22.16ex/s][A[A[A
preprocess datasets #0: 88%|████████▊ | 1980/2259 [01:06<00:10, 25.85ex/s]
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preprocess datasets #4: 92%|█████████▏| 2071/2258 [01:06<00:05, 37.25ex/s][A[A[A[A
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preprocess datasets #3: 90%|████████▉ | 2023/2258 [01:06<00:10, 23.38ex/s][A[A[A
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preprocess datasets #1: 86%|████████▌ | 1937/2258 [01:06<00:11, 28.12ex/s][A
preprocess datasets #0: 88%|████████▊ | 1983/2259 [01:06<00:11, 24.50ex/s]
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preprocess datasets #4: 92%|█████████▏| 2077/2258 [01:06<00:04, 41.37ex/s][A[A[A[A
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preprocess datasets #3: 90%|████████▉ | 2028/2258 [01:06<00:07, 29.20ex/s][A[A[A
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preprocess datasets #1: 86%|████████▌ | 1940/2258 [01:06<00:12, 25.07ex/s][A
preprocess datasets #0: 88%|████████▊ | 1987/2259 [01:06<00:10, 27.17ex/s]
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preprocess datasets #4: 92%|█████████▏| 2082/2258 [01:06<00:04, 42.30ex/s][A[A[A[A
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preprocess datasets #3: 90%|████████▉ | 2032/2258 [01:06<00:07, 30.16ex/s][A[A[A
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preprocess datasets #1: 86%|████████▌ | 1943/2258 [01:06<00:12, 25.99ex/s][A
preprocess datasets #0: 88%|████████▊ | 1990/2259 [01:06<00:09, 27.52ex/s]
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preprocess datasets #2: 89%|████████▊ | 2000/2258 [01:06<00:15, 16.59ex/s][A[A
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preprocess datasets #4: 92%|█████████▏| 2087/2258 [01:06<00:04, 37.97ex/s][A[A[A[A
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preprocess datasets #3: 90%|█████████ | 2036/2258 [01:06<00:07, 29.00ex/s][A[A[A
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preprocess datasets #1: 86%|████████▌ | 1946/2258 [01:06<00:13, 22.89ex/s][A
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preprocess datasets #4: 93%|█████████▎| 2092/2258 [01:06<00:04, 40.62ex/s][A[A[A[A
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preprocess datasets #2: 89%|████████▉ | 2004/2258 [01:06<00:13, 18.77ex/s][A[A
+
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+
preprocess datasets #3: 90%|█████���███ | 2040/2258 [01:06<00:06, 31.39ex/s][A[A[A
preprocess datasets #0: 88%|████████▊ | 1993/2259 [01:06<00:11, 23.51ex/s]
+
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preprocess datasets #2: 89%|████████▉ | 2008/2258 [01:06<00:11, 21.90ex/s][A[A
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+
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preprocess datasets #4: 93%|█████████▎| 2098/2258 [01:06<00:03, 43.38ex/s][A[A[A[A
preprocess datasets #0: 88%|████████▊ | 1996/2259 [01:06<00:10, 24.15ex/s]
+
preprocess datasets #1: 86%|████████▋ | 1949/2258 [01:06<00:13, 22.28ex/s][A
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preprocess datasets #3: 91%|█████████ | 2044/2258 [01:06<00:07, 28.50ex/s][A[A[A
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preprocess datasets #2: 89%|████████▉ | 2012/2258 [01:06<00:10, 23.41ex/s][A[A
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preprocess datasets #4: 93%|█████████▎| 2103/2258 [01:06<00:03, 42.46ex/s][A[A[A[A
preprocess datasets #0: 88%|████████▊ | 1999/2259 [01:06<00:11, 23.63ex/s]
+
preprocess datasets #1: 86%|████████▋ | 1952/2258 [01:06<00:13, 22.10ex/s][A
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preprocess datasets #3: 91%|█████████ | 2048/2258 [01:06<00:07, 26.60ex/s][A[A[A
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preprocess datasets #4: 93%|█████████▎| 2108/2258 [01:06<00:03, 42.83ex/s][A[A[A[A
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preprocess datasets #1: 87%|████████▋ | 1957/2258 [01:07<00:11, 25.88ex/s][A
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preprocess datasets #2: 89%|████████▉ | 2016/2258 [01:07<00:10, 22.09ex/s][A[A
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+
preprocess datasets #3: 91%|█████████ | 2052/2258 [01:07<00:06, 29.50ex/s][A[A[A
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preprocess datasets #1: 87%|████████▋ | 1962/2258 [01:07<00:09, 30.96ex/s][A
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preprocess datasets #2: 89%|████████▉ | 2020/2258 [01:07<00:10, 23.15ex/s][A[A
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preprocess datasets #3: 91%|█████████ | 2056/2258 [01:07<00:06, 28.87ex/s][A[A[A
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preprocess datasets #4: 94%|█████████▎| 2113/2258 [01:07<00:04, 31.62ex/s][A[A[A[A
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preprocess datasets #1: 87%|████████▋ | 1966/2258 [01:07<00:09, 29.33ex/s][A
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preprocess datasets #3: 91%|█████████▏| 2061/2258 [01:07<00:06, 32.53ex/s][A[A[A
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preprocess datasets #2: 90%|████████▉ | 2025/2258 [01:07<00:08, 26.13ex/s][A[A
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preprocess datasets #4: 94%|█████████▍| 2117/2258 [01:07<00:04, 29.68ex/s][A[A[A[A
+
preprocess datasets #1: 87%|████████▋ | 1970/2258 [01:07<00:09, 31.07ex/s][A
+
+
preprocess datasets #2: 90%|████████▉ | 2028/2258 [01:07<00:08, 26.62ex/s][A[A
preprocess datasets #0: 89%|████████▊ | 2002/2259 [01:07<00:23, 11.00ex/s]
+
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preprocess datasets #3: 91%|█████████▏| 2065/2258 [01:07<00:06, 28.29ex/s][A[A[A
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preprocess datasets #4: 94%|█████████▍| 2121/2258 [01:07<00:04, 29.04ex/s][A[A[A[A
+
preprocess datasets #1: 87%|████████▋ | 1974/2258 [01:07<00:09, 29.09ex/s][A
+
+
preprocess datasets #2: 90%|████████▉ | 2031/2258 [01:07<00:08, 25.52ex/s][A[A
preprocess datasets #0: 89%|████████▉ | 2005/2259 [01:07<00:19, 13.10ex/s]
+
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preprocess datasets #4: 94%|█████████▍| 2125/2258 [01:07<00:04, 30.81ex/s][A[A[A[A
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preprocess datasets #3: 92%|█████████▏| 2069/2258 [01:07<00:06, 28.38ex/s][A[A[A
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preprocess datasets #2: 90%|█████████ | 2034/2258 [01:07<00:08, 26.41ex/s][A[A
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preprocess datasets #4: 94%|█████████▍| 2130/2258 [01:07<00:03, 33.78ex/s][A[A[A[A
+
preprocess datasets #1: 88%|████████▊ | 1978/2258 [01:07<00:11, 25.07ex/s][A
preprocess datasets #0: 89%|████████▉ | 2008/2259 [01:07<00:17, 14.67ex/s]
+
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preprocess datasets #3: 92%|█████████▏| 2073/2258 [01:07<00:06, 28.07ex/s][A[A[A
+
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preprocess datasets #2: 90%|█████████ | 2037/2258 [01:07<00:08, 26.52ex/s][A[A
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preprocess datasets #4: 95%|█████████▍| 2134/2258 [01:07<00:03, 34.89ex/s][A[A[A[A
+
preprocess datasets #1: 88%|████████▊ | 1981/2258 [01:07<00:11, 24.73ex/s][A
preprocess datasets #0: 89%|████████▉ | 2011/2259 [01:07<00:15, 15.95ex/s]
+
+
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preprocess datasets #3: 92%|█████████▏| 2077/2258 [01:07<00:06, 29.13ex/s][A[A[A
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preprocess datasets #2: 90%|█████████ | 2040/2258 [01:07<00:08, 24.67ex/s][A[A
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preprocess datasets #4: 95%|█████████▍| 2138/2258 [01:07<00:03, 33.13ex/s][A[A[A[A
+
preprocess datasets #1: 88%|████████▊ | 1985/2258 [01:08<00:10, 26.42ex/s][A
preprocess datasets #0: 89%|████████▉ | 2015/2259 [01:08<00:12, 19.63ex/s]
+
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preprocess datasets #3: 92%|█████████▏| 2080/2258 [01:08<00:06, 27.42ex/s][A[A[A
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preprocess datasets #2: 90%|█████████ | 2043/2258 [01:08<00:08, 23.92ex/s][A[A
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preprocess datasets #4: 95%|█████████▍| 2143/2258 [01:08<00:03, 35.07ex/s][A[A[A[A
preprocess datasets #0: 89%|████████▉ | 2020/2259 [01:08<00:09, 25.69ex/s]
+
preprocess datasets #1: 88%|████████▊ | 1989/2258 [01:08<00:09, 27.59ex/s][A
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preprocess datasets #3: 92%|█████████▏| 2084/2258 [01:08<00:05, 29.60ex/s][A[A[A
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preprocess datasets #4: 95%|█████████▌| 2148/2258 [01:08<00:02, 37.91ex/s][A[A[A[A
+
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preprocess datasets #2: 91%|█████████ | 2046/2258 [01:08<00:09, 21.45ex/s][A[A
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preprocess datasets #1: 88%|████████▊ | 1993/2258 [01:08<00:09, 28.69ex/s][A
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preprocess datasets #3: 92%|█████████▏| 2088/2258 [01:08<00:06, 25.05ex/s][A[A[A
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preprocess datasets #1: 88%|████████▊ | 1996/2258 [01:08<00:09, 28.63ex/s][A
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preprocess datasets #4: 95%|█████████▌| 2152/2258 [01:08<00:03, 32.88ex/s][A[A[A[A
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preprocess datasets #2: 91%|█████████ | 2049/2258 [01:08<00:09, 21.46ex/s][A[A
preprocess datasets #0: 90%|████████▉ | 2024/2259 [01:08<00:11, 21.10ex/s]
+
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preprocess datasets #3: 93%|█████████▎| 2094/2258 [01:08<00:05, 30.61ex/s][A[A[A
preprocess datasets #0: 90%|████████▉ | 2027/2259 [01:08<00:10, 22.66ex/s]
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preprocess datasets #2: 91%|█████████ | 2054/2258 [01:08<00:07, 27.03ex/s][A[A
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preprocess datasets #4: 95%|█████████▌| 2156/2258 [01:08<00:03, 30.73ex/s][A[A[A[A
+
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preprocess datasets #2: 91%|█████████ | 2057/2258 [01:08<00:07, 27.27ex/s][A[A
preprocess datasets #0: 90%|████████▉ | 2030/2259 [01:08<00:09, 23.29ex/s]
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preprocess datasets #3: 93%|█████████▎| 2098/2258 [01:08<00:05, 31.25ex/s][A[A[A
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preprocess datasets #4: 96%|█████████▌| 2160/2258 [01:08<00:03, 31.19ex/s][A[A[A[A
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preprocess datasets #2: 91%|█████████▏| 2061/2258 [01:08<00:06, 28.79ex/s][A[A
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preprocess datasets #3: 93%|█████████▎| 2102/2258 [01:08<00:04, 31.58ex/s][A[A[A
preprocess datasets #0: 90%|█████████ | 2035/2259 [01:08<00:08, 27.47ex/s]
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preprocess datasets #4: 96%|█████████▌| 2164/2258 [01:08<00:03, 28.68ex/s][A[A[A[A
preprocess datasets #0: 90%|█████████ | 2040/2259 [01:08<00:07, 30.89ex/s]
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preprocess datasets #3: 93%|█████████▎| 2106/2258 [01:08<00:04, 30.64ex/s][A[A[A
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preprocess datasets #2: 91%|█████████▏| 2064/2258 [01:08<00:07, 24.76ex/s][A[A
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preprocess datasets #4: 96%|█████████▌| 2167/2258 [01:08<00:03, 26.82ex/s][A[A[A[A
preprocess datasets #0: 90%|█████████ | 2044/2259 [01:09<00:07, 29.71ex/s]
+
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preprocess datasets #2: 92%|█████████▏| 2068/2258 [01:09<00:07, 26.34ex/s][A[A
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preprocess datasets #3: 93%|█████████▎| 2110/2258 [01:09<00:05, 27.67ex/s][A[A[A
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preprocess datasets #4: 96%|█████████▌| 2170/2258 [01:09<00:03, 25.03ex/s][A[A[A[A
preprocess datasets #0: 91%|█████████ | 2049/2259 [01:09<00:06, 32.55ex/s]
+
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preprocess datasets #2: 92%|█████████▏| 2073/2258 [01:09<00:06, 29.91ex/s][A[A
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preprocess datasets #4: 96%|█████████▌| 2173/2258 [01:09<00:03, 26.01ex/s][A[A[A[A
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preprocess datasets #3: 94%|█████████▎| 2113/2258 [01:09<00:05, 25.46ex/s][A[A[A
preprocess datasets #0: 91%|█████████ | 2053/2259 [01:09<00:06, 30.54ex/s]
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preprocess datasets #4: 96%|█████████▋| 2178/2258 [01:09<00:02, 31.59ex/s][A[A[A[A
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preprocess datasets #2: 92%|█████████▏| 2077/2258 [01:09<00:06, 28.40ex/s][A[A
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preprocess datasets #3: 94%|█████████▎| 2116/2258 [01:09<00:05, 24.86ex/s][A[A[A
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preprocess datasets #4: 97%|█████████▋| 2184/2258 [01:09<00:01, 38.20ex/s][A[A[A[A
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preprocess datasets #2: 92%|█████████▏| 2081/2258 [01:09<00:05, 29.95ex/s][A[A
preprocess datasets #0: 91%|█████████ | 2057/2259 [01:09<00:06, 29.93ex/s]
+
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preprocess datasets #3: 94%|█████████▍| 2119/2258 [01:09<00:05, 25.69ex/s][A[A[A
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preprocess datasets #1: 89%|████████▊ | 2000/2258 [01:09<00:28, 9.08ex/s][A
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preprocess datasets #4: 97%|█████████▋| 2190/2258 [01:09<00:01, 42.79ex/s][A[A[A[A
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preprocess datasets #1: 89%|████████▉ | 2004/2258 [01:09<00:21, 11.94ex/s][A
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+
preprocess datasets #2: 92%|█████████▏| 2085/2258 [01:09<00:05, 30.41ex/s][A[A
preprocess datasets #0: 91%|█████████ | 2061/2259 [01:09<00:06, 30.05ex/s]
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preprocess datasets #3: 94%|█████████▍| 2123/2258 [01:09<00:05, 24.53ex/s][A[A[A
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preprocess datasets #4: 97%|█████████▋| 2196/2258 [01:09<00:01, 44.54ex/s][A[A[A[A
+
preprocess datasets #1: 89%|████████▉ | 2007/2258 [01:09<00:18, 13.85ex/s][A
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+
preprocess datasets #2: 93%|█████████▎| 2089/2258 [01:09<00:05, 30.53ex/s][A[A
preprocess datasets #0: 91%|█████████▏| 2065/2259 [01:09<00:06, 28.91ex/s]
+
preprocess datasets #1: 89%|████████▉ | 2010/2258 [01:09<00:15, 15.50ex/s][A
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preprocess datasets #4: 97%|█████████▋| 2201/2258 [01:09<00:01, 40.79ex/s][A[A[A[A
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preprocess datasets #3: 94%|█████████▍| 2127/2258 [01:09<00:05, 23.56ex/s][A[A[A
preprocess datasets #0: 92%|█████████▏| 2070/2259 [01:09<00:05, 32.09ex/s]
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+
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preprocess datasets #1: 100%|██████████| 2258/2258 [01:17<00:00, 28.96ex/s]
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+ array = librosa.resample(array, sampling_rate, self.sampling_rate, res_type="kaiser_best")
+/idiap/user/jzuluaga/miniconda3/envs/w2v2/lib/python3.10/site-packages/datasets/features/audio.py:279: FutureWarning: Pass orig_sr=8000, target_sr=16000 as keyword args. From version 0.10 passing these as positional arguments will result in an error
+ array = librosa.resample(array, sampling_rate, self.sampling_rate, res_type="kaiser_best")
+/idiap/user/jzuluaga/miniconda3/envs/w2v2/lib/python3.10/site-packages/datasets/features/audio.py:279: FutureWarning: Pass orig_sr=8000, target_sr=16000 as keyword args. From version 0.10 passing these as positional arguments will result in an error
+ array = librosa.resample(array, sampling_rate, self.sampling_rate, res_type="kaiser_best")
+/idiap/user/jzuluaga/miniconda3/envs/w2v2/lib/python3.10/site-packages/datasets/features/audio.py:279: FutureWarning: Pass orig_sr=8000, target_sr=16000 as keyword args. From version 0.10 passing these as positional arguments will result in an error
+ array = librosa.resample(array, sampling_rate, self.sampling_rate, res_type="kaiser_best")
+/idiap/user/jzuluaga/miniconda3/envs/w2v2/lib/python3.10/site-packages/datasets/features/audio.py:279: FutureWarning: Pass orig_sr=8000, target_sr=16000 as keyword args. From version 0.10 passing these as positional arguments will result in an error
+ array = librosa.resample(array, sampling_rate, self.sampling_rate, res_type="kaiser_best")
+
+
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preprocess datasets #2: 0%| | 1/564 [00:01<13:17, 1.42s/ex][A[A
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+ array = librosa.resample(array, sampling_rate, self.sampling_rate, res_type="kaiser_best")
+/idiap/user/jzuluaga/miniconda3/envs/w2v2/lib/python3.10/site-packages/datasets/features/audio.py:279: FutureWarning: Pass orig_sr=8000, target_sr=16000 as keyword args. From version 0.10 passing these as positional arguments will result in an error
+ array = librosa.resample(array, sampling_rate, self.sampling_rate, res_type="kaiser_best")
+
preprocess datasets #0: 0%| | 1/565 [00:01<13:35, 1.45s/ex]/idiap/user/jzuluaga/miniconda3/envs/w2v2/lib/python3.10/site-packages/datasets/features/audio.py:279: FutureWarning: Pass orig_sr=8000, target_sr=16000 as keyword args. From version 0.10 passing these as positional arguments will result in an error
+ array = librosa.resample(array, sampling_rate, self.sampling_rate, res_type="kaiser_best")
+
+
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+ array = librosa.resample(array, sampling_rate, self.sampling_rate, res_type="kaiser_best")
+
+
preprocess datasets #1: 0%| | 1/565 [00:01<13:51, 1.47s/ex][A/idiap/user/jzuluaga/miniconda3/envs/w2v2/lib/python3.10/site-packages/datasets/features/audio.py:279: FutureWarning: Pass orig_sr=8000, target_sr=16000 as keyword args. From version 0.10 passing these as positional arguments will result in an error
+ array = librosa.resample(array, sampling_rate, self.sampling_rate, res_type="kaiser_best")
+
+
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preprocess datasets #3: 1%| | 4/564 [00:01<02:43, 3.42ex/s][A[A[A
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preprocess datasets #0: 2%|▏ | 12/565 [00:01<00:49, 11.07ex/s]
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preprocess datasets #0: 6%|▌ | 34/565 [00:02<00:21, 24.39ex/s]
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+Feature extractor saved in experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/preprocessor_config.json
+tokenizer config file saved in experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/tokenizer_config.json
+Special tokens file saved in experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/special_tokens_map.json
+added tokens file saved in experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/added_tokens.json
+Configuration saved in experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/config.json
+loading configuration file experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/preprocessor_config.json
+loading configuration file experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/config.json
+Model config Wav2Vec2Config {
+ "_name_or_path": "experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/",
+ "activation_dropout": 0.0,
+ "adapter_kernel_size": 3,
+ "adapter_stride": 2,
+ "add_adapter": false,
+ "apply_spec_augment": true,
+ "architectures": [
+ "Wav2Vec2ForCTC"
+ ],
+ "attention_dropout": 0.0,
+ "bos_token_id": 1,
+ "classifier_proj_size": 256,
+ "codevector_dim": 256,
+ "contrastive_logits_temperature": 0.1,
+ "conv_bias": true,
+ "conv_dim": [
+ 512,
+ 512,
+ 512,
+ 512,
+ 512,
+ 512,
+ 512
+ ],
+ "conv_kernel": [
+ 10,
+ 3,
+ 3,
+ 3,
+ 3,
+ 2,
+ 2
+ ],
+ "conv_stride": [
+ 5,
+ 2,
+ 2,
+ 2,
+ 2,
+ 2,
+ 2
+ ],
+ "ctc_loss_reduction": "mean",
+ "ctc_zero_infinity": true,
+ "diversity_loss_weight": 0.1,
+ "do_stable_layer_norm": true,
+ "eos_token_id": 2,
+ "feat_extract_activation": "gelu",
+ "feat_extract_dropout": 0.0,
+ "feat_extract_norm": "layer",
+ "feat_proj_dropout": 0.05,
+ "feat_quantizer_dropout": 0.0,
+ "final_dropout": 0.0,
+ "hidden_act": "gelu",
+ "hidden_dropout": 0.0,
+ "hidden_dropout_prob": 0.1,
+ "hidden_size": 1024,
+ "initializer_range": 0.02,
+ "intermediate_size": 4096,
+ "layer_norm_eps": 1e-05,
+ "layerdrop": 0.0,
+ "mask_feature_length": 12,
+ "mask_feature_min_masks": 0,
+ "mask_feature_prob": 0.0,
+ "mask_time_length": 12,
+ "mask_time_min_masks": 2,
+ "mask_time_prob": 0.075,
+ "model_type": "wav2vec2",
+ "num_adapter_layers": 3,
+ "num_attention_heads": 16,
+ "num_codevector_groups": 2,
+ "num_codevectors_per_group": 320,
+ "num_conv_pos_embedding_groups": 16,
+ "num_conv_pos_embeddings": 128,
+ "num_feat_extract_layers": 7,
+ "num_hidden_layers": 24,
+ "num_negatives": 100,
+ "output_hidden_size": 1024,
+ "pad_token_id": 28,
+ "proj_codevector_dim": 256,
+ "tdnn_dilation": [
+ 1,
+ 2,
+ 3,
+ 1,
+ 1
+ ],
+ "tdnn_dim": [
+ 512,
+ 512,
+ 512,
+ 512,
+ 1500
+ ],
+ "tdnn_kernel": [
+ 5,
+ 3,
+ 3,
+ 1,
+ 1
+ ],
+ "transformers_version": "4.24.0",
+ "use_weighted_layer_sum": false,
+ "vocab_size": 31,
+ "xvector_output_dim": 512
+}
+
+loading configuration file experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/preprocessor_config.json
+Feature extractor Wav2Vec2FeatureExtractor {
+ "do_normalize": true,
+ "feature_extractor_type": "Wav2Vec2FeatureExtractor",
+ "feature_size": 1,
+ "padding_side": "right",
+ "padding_value": 0.0,
+ "return_attention_mask": true,
+ "sampling_rate": 16000
+}
+
+loading file vocab.json
+loading file tokenizer_config.json
+loading file added_tokens.json
+loading file special_tokens_map.json
+Adding <s> to the vocabulary
+Adding </s> to the vocabulary
+max_steps is given, it will override any value given in num_train_epochs
+Using cuda_amp half precision backend
+The following columns in the training set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length. If input_length are not expected by `Wav2Vec2ForCTC.forward`, you can safely ignore this message.
+/idiap/user/jzuluaga/miniconda3/envs/w2v2/lib/python3.10/site-packages/transformers/optimization.py:306: FutureWarning: This implementation of AdamW is deprecated and will be removed in a future version. Use the PyTorch implementation torch.optim.AdamW instead, or set `no_deprecation_warning=True` to disable this warning
+ warnings.warn(
+***** Running training *****
+ Num examples = 11291
+ Num Epochs = 22
+ Instantaneous batch size per device = 24
+ Total train batch size (w. parallel, distributed & accumulation) = 24
+ Gradient Accumulation steps = 1
+ Total optimization steps = 10000
+ Number of trainable parameters = 311260319
+
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5%|▌ | 500/10000 [07:31<2:07:58, 1.24it/s]The following columns in the evaluation set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length. If input_length are not expected by `Wav2Vec2ForCTC.forward`, you can safely ignore this message.
+***** Running Evaluation *****
+ Num examples = 2822
+ Batch size = 12
+
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[A
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[A
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10%|█ | 1000/10000 [16:14<3:35:28, 1.44s/it]The following columns in the evaluation set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length. If input_length are not expected by `Wav2Vec2ForCTC.forward`, you can safely ignore this message.
+***** Running Evaluation *****
+ Num examples = 2822
+ Batch size = 12
+{'eval_loss': 2.901623249053955, 'eval_wer': 0.9995142002989537, 'eval_runtime': 78.4215, 'eval_samples_per_second': 35.985, 'eval_steps_per_second': 3.009, 'epoch': 1.06}
+{'loss': 2.877, 'learning_rate': 9.970000000000001e-05, 'epoch': 2.12}
+
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[A
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[ASaving model checkpoint to experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/checkpoint-1000
+Configuration saved in experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/checkpoint-1000/config.json
+Model weights saved in experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/checkpoint-1000/pytorch_model.bin
+Feature extractor saved in experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/checkpoint-1000/preprocessor_config.json
+
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15%|█▌ | 1500/10000 [25:02<1:31:23, 1.55it/s]The following columns in the evaluation set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length. If input_length are not expected by `Wav2Vec2ForCTC.forward`, you can safely ignore this message.
+***** Running Evaluation *****
+ Num examples = 2822
+ Batch size = 12
+{'eval_loss': 0.981178343296051, 'eval_wer': 0.3484678624813154, 'eval_runtime': 78.2116, 'eval_samples_per_second': 36.082, 'eval_steps_per_second': 3.017, 'epoch': 2.12}
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[A
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[A
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20%|██ | 2000/10000 [33:42<2:25:44, 1.09s/it]The following columns in the evaluation set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length. If input_length are not expected by `Wav2Vec2ForCTC.forward`, you can safely ignore this message.
+***** Running Evaluation *****
+ Num examples = 2822
+ Batch size = 12
+{'eval_loss': 0.784228503704071, 'eval_wer': 0.273168908819133, 'eval_runtime': 78.8199, 'eval_samples_per_second': 35.803, 'eval_steps_per_second': 2.994, 'epoch': 3.18}
+{'loss': 0.7834, 'learning_rate': 8.892222222222223e-05, 'epoch': 4.25}
+
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[A
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[ASaving model checkpoint to experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/checkpoint-2000
+Configuration saved in experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/checkpoint-2000/config.json
+Model weights saved in experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/checkpoint-2000/pytorch_model.bin
+Feature extractor saved in experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/checkpoint-2000/preprocessor_config.json
+Deleting older checkpoint [experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/checkpoint-1000] due to args.save_total_limit
+
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25%|██▌ | 2500/10000 [42:25<49:48, 2.51it/s]The following columns in the evaluation set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length. If input_length are not expected by `Wav2Vec2ForCTC.forward`, you can safely ignore this message.
+***** Running Evaluation *****
+ Num examples = 2822
+ Batch size = 12
+{'eval_loss': 0.6962451934814453, 'eval_wer': 0.21917040358744394, 'eval_runtime': 78.959, 'eval_samples_per_second': 35.74, 'eval_steps_per_second': 2.989, 'epoch': 4.25}
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30%|███ | 3000/10000 [51:11<1:43:26, 1.13it/s]The following columns in the evaluation set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length. If input_length are not expected by `Wav2Vec2ForCTC.forward`, you can safely ignore this message.
+***** Running Evaluation *****
+ Num examples = 2822
+ Batch size = 12
+{'eval_loss': 0.6526582837104797, 'eval_wer': 0.20418535127055307, 'eval_runtime': 78.1018, 'eval_samples_per_second': 36.132, 'eval_steps_per_second': 3.022, 'epoch': 5.31}
+{'loss': 0.6084, 'learning_rate': 7.78111111111111e-05, 'epoch': 6.37}
+
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[A
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[ASaving model checkpoint to experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/checkpoint-3000
+Configuration saved in experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/checkpoint-3000/config.json
+Model weights saved in experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/checkpoint-3000/pytorch_model.bin
+Feature extractor saved in experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/checkpoint-3000/preprocessor_config.json
+Deleting older checkpoint [experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/checkpoint-2000] due to args.save_total_limit
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35%|███▌ | 3500/10000 [59:50<2:13:30, 1.23s/it]The following columns in the evaluation set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length. If input_length are not expected by `Wav2Vec2ForCTC.forward`, you can safely ignore this message.
+***** Running Evaluation *****
+ Num examples = 2822
+ Batch size = 12
+{'eval_loss': 0.6220057606697083, 'eval_wer': 0.19715994020926755, 'eval_runtime': 79.4519, 'eval_samples_per_second': 35.518, 'eval_steps_per_second': 2.97, 'epoch': 6.37}
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40%|████ | 4000/10000 [1:08:34<1:15:15, 1.33it/s]The following columns in the evaluation set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length. If input_length are not expected by `Wav2Vec2ForCTC.forward`, you can safely ignore this message.
+***** Running Evaluation *****
+ Num examples = 2822
+ Batch size = 12
+{'eval_loss': 0.6441554427146912, 'eval_wer': 0.19338565022421525, 'eval_runtime': 80.6733, 'eval_samples_per_second': 34.981, 'eval_steps_per_second': 2.925, 'epoch': 7.43}
+{'loss': 0.5147, 'learning_rate': 6.670000000000001e-05, 'epoch': 8.49}
+
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[A
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[ASaving model checkpoint to experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/checkpoint-4000
+Configuration saved in experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/checkpoint-4000/config.json
+Model weights saved in experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/checkpoint-4000/pytorch_model.bin
+Feature extractor saved in experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/checkpoint-4000/preprocessor_config.json
+Deleting older checkpoint [experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/checkpoint-3000] due to args.save_total_limit
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45%|████▌ | 4500/10000 [1:17:36<2:02:14, 1.33s/it]The following columns in the evaluation set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length. If input_length are not expected by `Wav2Vec2ForCTC.forward`, you can safely ignore this message.
+***** Running Evaluation *****
+ Num examples = 2822
+ Batch size = 12
+{'eval_loss': 0.6793447732925415, 'eval_wer': 0.19495515695067264, 'eval_runtime': 80.545, 'eval_samples_per_second': 35.036, 'eval_steps_per_second': 2.93, 'epoch': 8.49}
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50%|█████ | 5000/10000 [1:26:17<43:24, 1.92it/s]The following columns in the evaluation set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length. If input_length are not expected by `Wav2Vec2ForCTC.forward`, you can safely ignore this message.
+***** Running Evaluation *****
+ Num examples = 2822
+ Batch size = 12
+{'eval_loss': 0.6431596875190735, 'eval_wer': 0.19200298953662182, 'eval_runtime': 83.1308, 'eval_samples_per_second': 33.947, 'eval_steps_per_second': 2.839, 'epoch': 9.55}
+{'loss': 0.4566, 'learning_rate': 5.558888888888889e-05, 'epoch': 10.62}
+
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[A
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[ASaving model checkpoint to experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/checkpoint-5000
+Configuration saved in experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/checkpoint-5000/config.json
+Model weights saved in experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/checkpoint-5000/pytorch_model.bin
+Feature extractor saved in experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/checkpoint-5000/preprocessor_config.json
+Deleting older checkpoint [experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/checkpoint-4000] due to args.save_total_limit
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55%|█████▌ | 5500/10000 [1:35:09<1:14:07, 1.01it/s]The following columns in the evaluation set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length. If input_length are not expected by `Wav2Vec2ForCTC.forward`, you can safely ignore this message.
+***** Running Evaluation *****
+ Num examples = 2822
+ Batch size = 12
+{'eval_loss': 0.6605134010314941, 'eval_wer': 0.1853139013452915, 'eval_runtime': 80.2378, 'eval_samples_per_second': 35.17, 'eval_steps_per_second': 2.941, 'epoch': 10.62}
+
+
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[A
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60%|██████ | 6000/10000 [1:43:33<23:17, 2.86it/s]The following columns in the evaluation set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length. If input_length are not expected by `Wav2Vec2ForCTC.forward`, you can safely ignore this message.
+***** Running Evaluation *****
+ Num examples = 2822
+ Batch size = 12
+{'eval_loss': 0.6392588019371033, 'eval_wer': 0.18658445440956653, 'eval_runtime': 78.2211, 'eval_samples_per_second': 36.077, 'eval_steps_per_second': 3.017, 'epoch': 11.68}
+{'loss': 0.4155, 'learning_rate': 4.448888888888889e-05, 'epoch': 12.74}
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[A
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[ASaving model checkpoint to experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/checkpoint-6000
+Configuration saved in experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/checkpoint-6000/config.json
+Model weights saved in experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/checkpoint-6000/pytorch_model.bin
+Feature extractor saved in experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/checkpoint-6000/preprocessor_config.json
+Deleting older checkpoint [experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/checkpoint-5000] due to args.save_total_limit
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65%|██████▌ | 6500/10000 [1:52:19<48:09, 1.21it/s]The following columns in the evaluation set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length. If input_length are not expected by `Wav2Vec2ForCTC.forward`, you can safely ignore this message.
+***** Running Evaluation *****
+ Num examples = 2822
+ Batch size = 12
+{'eval_loss': 0.6917754411697388, 'eval_wer': 0.18030642750373693, 'eval_runtime': 78.1406, 'eval_samples_per_second': 36.114, 'eval_steps_per_second': 3.02, 'epoch': 12.74}
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70%|███████ | 7000/10000 [2:00:48<1:09:36, 1.39s/it]The following columns in the evaluation set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length. If input_length are not expected by `Wav2Vec2ForCTC.forward`, you can safely ignore this message.
+***** Running Evaluation *****
+ Num examples = 2822
+ Batch size = 12
+{'eval_loss': 0.6514243483543396, 'eval_wer': 0.17911061285500748, 'eval_runtime': 78.7289, 'eval_samples_per_second': 35.845, 'eval_steps_per_second': 2.998, 'epoch': 13.8}
+{'loss': 0.372, 'learning_rate': 3.337777777777778e-05, 'epoch': 14.86}
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[A
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[ASaving model checkpoint to experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/checkpoint-7000
+Configuration saved in experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/checkpoint-7000/config.json
+Model weights saved in experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/checkpoint-7000/pytorch_model.bin
+Feature extractor saved in experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/checkpoint-7000/preprocessor_config.json
+Deleting older checkpoint [experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/checkpoint-6000] due to args.save_total_limit
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75%|███████▌ | 7500/10000 [2:09:36<28:45, 1.45it/s]The following columns in the evaluation set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length. If input_length are not expected by `Wav2Vec2ForCTC.forward`, you can safely ignore this message.
+***** Running Evaluation *****
+ Num examples = 2822
+ Batch size = 12
+{'eval_loss': 0.7009950876235962, 'eval_wer': 0.1851270553064275, 'eval_runtime': 78.8286, 'eval_samples_per_second': 35.799, 'eval_steps_per_second': 2.994, 'epoch': 14.86}
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80%|████████ | 8000/10000 [2:18:12<25:30, 1.31it/s]The following columns in the evaluation set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length. If input_length are not expected by `Wav2Vec2ForCTC.forward`, you can safely ignore this message.
+***** Running Evaluation *****
+ Num examples = 2822
+ Batch size = 12
+{'eval_loss': 0.6824212670326233, 'eval_wer': 0.17858744394618833, 'eval_runtime': 79.8558, 'eval_samples_per_second': 35.339, 'eval_steps_per_second': 2.955, 'epoch': 15.92}
+{'loss': 0.3368, 'learning_rate': 2.2277777777777778e-05, 'epoch': 16.99}
+
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[A
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[ASaving model checkpoint to experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/checkpoint-8000
+Configuration saved in experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/checkpoint-8000/config.json
+Model weights saved in experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/checkpoint-8000/pytorch_model.bin
+Feature extractor saved in experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/checkpoint-8000/preprocessor_config.json
+Deleting older checkpoint [experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/checkpoint-7000] due to args.save_total_limit
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85%|████████▌ | 8500/10000 [2:27:04<23:59, 1.04it/s]The following columns in the evaluation set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length. If input_length are not expected by `Wav2Vec2ForCTC.forward`, you can safely ignore this message.
+***** Running Evaluation *****
+ Num examples = 2822
+ Batch size = 12
+{'eval_loss': 0.6895105838775635, 'eval_wer': 0.1780269058295964, 'eval_runtime': 81.107, 'eval_samples_per_second': 34.794, 'eval_steps_per_second': 2.91, 'epoch': 16.99}
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90%|█████████ | 9000/10000 [2:35:37<13:49, 1.21it/s]The following columns in the evaluation set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length. If input_length are not expected by `Wav2Vec2ForCTC.forward`, you can safely ignore this message.
+***** Running Evaluation *****
+ Num examples = 2822
+ Batch size = 12
+{'eval_loss': 0.7150452136993408, 'eval_wer': 0.17589686098654708, 'eval_runtime': 79.9454, 'eval_samples_per_second': 35.299, 'eval_steps_per_second': 2.952, 'epoch': 18.05}
+{'loss': 0.3244, 'learning_rate': 1.1177777777777779e-05, 'epoch': 19.11}
+
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[A
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[ASaving model checkpoint to experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/checkpoint-9000
+Configuration saved in experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/checkpoint-9000/config.json
+Model weights saved in experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/checkpoint-9000/pytorch_model.bin
+Feature extractor saved in experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/checkpoint-9000/preprocessor_config.json
+Deleting older checkpoint [experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/checkpoint-8000] due to args.save_total_limit
+
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95%|█████████▌| 9500/10000 [2:44:48<06:15, 1.33it/s]The following columns in the evaluation set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length. If input_length are not expected by `Wav2Vec2ForCTC.forward`, you can safely ignore this message.
+***** Running Evaluation *****
+ Num examples = 2822
+ Batch size = 12
+{'eval_loss': 0.7141156792640686, 'eval_wer': 0.17589686098654708, 'eval_runtime': 85.0058, 'eval_samples_per_second': 33.198, 'eval_steps_per_second': 2.776, 'epoch': 19.11}
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100%|██████████| 10000/10000 [2:53:18<00:00, 1.28s/it]The following columns in the evaluation set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length. If input_length are not expected by `Wav2Vec2ForCTC.forward`, you can safely ignore this message.
+***** Running Evaluation *****
+ Num examples = 2822
+ Batch size = 12
+{'eval_loss': 0.7225230932235718, 'eval_wer': 0.17556053811659192, 'eval_runtime': 77.8748, 'eval_samples_per_second': 36.238, 'eval_steps_per_second': 3.031, 'epoch': 20.17}
+{'loss': 0.2981, 'learning_rate': 6.666666666666667e-08, 'epoch': 21.23}
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[A
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[ASaving model checkpoint to experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/checkpoint-10000
+Configuration saved in experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/checkpoint-10000/config.json
+Model weights saved in experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/checkpoint-10000/pytorch_model.bin
+Feature extractor saved in experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/checkpoint-10000/preprocessor_config.json
+Deleting older checkpoint [experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/checkpoint-9000] due to args.save_total_limit
+
+
+Training completed. Do not forget to share your model on huggingface.co/models =)
+
+
+
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+Saving model checkpoint to experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/
+Configuration saved in experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/config.json
+Model weights saved in experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/pytorch_model.bin
+Feature extractor saved in experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/preprocessor_config.json
+{'eval_loss': 0.7286972403526306, 'eval_wer': 0.17556053811659192, 'eval_runtime': 78.6838, 'eval_samples_per_second': 35.865, 'eval_steps_per_second': 2.999, 'epoch': 21.23}
+{'train_runtime': 10488.9956, 'train_samples_per_second': 22.881, 'train_steps_per_second': 0.953, 'train_loss': 0.6986962738037109, 'epoch': 21.23}
+***** train metrics *****
+ epoch = 21.23
+ train_loss = 0.6987
+ train_runtime = 2:54:48.99
+ train_samples = 11291
+ train_samples_per_second = 22.881
+ train_steps_per_second = 0.953
+11/28/2022 18:11:22 - INFO - __main__ - *** Evaluate ***
+The following columns in the evaluation set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length. If input_length are not expected by `Wav2Vec2ForCTC.forward`, you can safely ignore this message.
+***** Running Evaluation *****
+ Num examples = 2822
+ Batch size = 12
+
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+Dropping the following result as it does not have all the necessary fields:
+{'metrics': [{'name': 'Wer', 'type': 'wer', 'value': 0.17556053811659192}]}
+***** eval metrics *****
+ epoch = 21.23
+ eval_loss = 0.7287
+ eval_runtime = 0:01:20.35
+ eval_samples = 2822
+ eval_samples_per_second = 35.119
+ eval_steps_per_second = 2.937
+ eval_wer = 0.1756
+# Accounting: time=10829 threads=1
+# Finished at Mon 28 Nov 18:12:44 CET 2022 with status 0