Priyanship commited on
Commit
320ec80
·
verified ·
1 Parent(s): 82581d1

End of training

Browse files
README.md CHANGED
@@ -1,8 +1,6 @@
1
  ---
2
  tags:
3
  - generated_from_trainer
4
- metrics:
5
- - wer
6
  model-index:
7
  - name: s300_shuff100
8
  results: []
@@ -11,14 +9,19 @@ model-index:
11
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
12
  should probably proofread and complete it, then remove this comment. -->
13
 
14
- [<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/priyanshipal/huggingface/runs/0evkescz)
15
  # s300_shuff100
16
 
17
  This model was trained from scratch on an unknown dataset.
18
  It achieves the following results on the evaluation set:
19
- - Loss: 1.5066
20
- - Cer: 0.3096
21
- - Wer: 0.4357
 
 
 
 
 
22
 
23
  ## Model description
24
 
@@ -49,13 +52,6 @@ The following hyperparameters were used during training:
49
  - training_steps: 1000
50
  - mixed_precision_training: Native AMP
51
 
52
- ### Training results
53
-
54
- | Training Loss | Epoch | Step | Validation Loss | Cer | Wer |
55
- |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
56
- | 0.9856 | 1.6 | 1000 | 1.5066 | 0.3096 | 0.4357 |
57
-
58
-
59
  ### Framework versions
60
 
61
  - Transformers 4.43.1
 
1
  ---
2
  tags:
3
  - generated_from_trainer
 
 
4
  model-index:
5
  - name: s300_shuff100
6
  results: []
 
9
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
10
  should probably proofread and complete it, then remove this comment. -->
11
 
12
+ [<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/priyanshipal/huggingface/runs/jw39kyll)
13
  # s300_shuff100
14
 
15
  This model was trained from scratch on an unknown dataset.
16
  It achieves the following results on the evaluation set:
17
+ - eval_loss: nan
18
+ - eval_model_preparation_time: 0.0044
19
+ - eval_cer: 1.0
20
+ - eval_wer: 1.0
21
+ - eval_runtime: 40.6214
22
+ - eval_samples_per_second: 14.081
23
+ - eval_steps_per_second: 0.886
24
+ - step: 0
25
 
26
  ## Model description
27
 
 
52
  - training_steps: 1000
53
  - mixed_precision_training: Native AMP
54
 
 
 
 
 
 
 
 
55
  ### Framework versions
56
 
57
  - Transformers 4.43.1
all_results.json CHANGED
@@ -1,12 +1,13 @@
1
  {
2
  "epoch": 1.6,
3
- "eval_cer": 0.30955352407101183,
4
- "eval_loss": 1.5066314935684204,
5
- "eval_runtime": 159.3193,
6
- "eval_samples": 3136,
7
- "eval_samples_per_second": 19.684,
8
- "eval_steps_per_second": 1.23,
9
- "eval_wer": 0.43571675485946765,
 
10
  "total_flos": 6.212261523683712e+18,
11
  "train_loss": 3.21392811447382,
12
  "train_runtime": 2133.1271,
 
1
  {
2
  "epoch": 1.6,
3
+ "eval_cer": 1.0,
4
+ "eval_loss": NaN,
5
+ "eval_model_preparation_time": 0.0044,
6
+ "eval_runtime": 40.6214,
7
+ "eval_samples": 572,
8
+ "eval_samples_per_second": 14.081,
9
+ "eval_steps_per_second": 0.886,
10
+ "eval_wer": 1.0,
11
  "total_flos": 6.212261523683712e+18,
12
  "train_loss": 3.21392811447382,
13
  "train_runtime": 2133.1271,
config.json CHANGED
@@ -9,7 +9,7 @@
9
  "architectures": [
10
  "Wav2Vec2ForCTC"
11
  ],
12
- "attention_dropout": 0.3,
13
  "bos_token_id": 1,
14
  "classifier_proj_size": 256,
15
  "codevector_dim": 256,
@@ -50,11 +50,11 @@
50
  "feat_extract_activation": "gelu",
51
  "feat_extract_dropout": 0.0,
52
  "feat_extract_norm": "layer",
53
- "feat_proj_dropout": 0.3,
54
  "feat_quantizer_dropout": 0.0,
55
  "final_dropout": 0.0,
56
  "hidden_act": "gelu",
57
- "hidden_dropout": 0.2,
58
  "hidden_dropout_prob": 0.1,
59
  "hidden_size": 1024,
60
  "initializer_range": 0.02,
 
9
  "architectures": [
10
  "Wav2Vec2ForCTC"
11
  ],
12
+ "attention_dropout": 0.0,
13
  "bos_token_id": 1,
14
  "classifier_proj_size": 256,
15
  "codevector_dim": 256,
 
50
  "feat_extract_activation": "gelu",
51
  "feat_extract_dropout": 0.0,
52
  "feat_extract_norm": "layer",
53
+ "feat_proj_dropout": 0.0,
54
  "feat_quantizer_dropout": 0.0,
55
  "final_dropout": 0.0,
56
  "hidden_act": "gelu",
57
+ "hidden_dropout": 0.0,
58
  "hidden_dropout_prob": 0.1,
59
  "hidden_size": 1024,
60
  "initializer_range": 0.02,
eval_results.json CHANGED
@@ -1,10 +1,10 @@
1
  {
2
- "epoch": 1.6,
3
- "eval_cer": 0.30955352407101183,
4
- "eval_loss": 1.5066314935684204,
5
- "eval_runtime": 159.3193,
6
- "eval_samples": 3136,
7
- "eval_samples_per_second": 19.684,
8
- "eval_steps_per_second": 1.23,
9
- "eval_wer": 0.43571675485946765
10
  }
 
1
  {
2
+ "eval_cer": 1.0,
3
+ "eval_loss": NaN,
4
+ "eval_model_preparation_time": 0.0044,
5
+ "eval_runtime": 40.6214,
6
+ "eval_samples": 572,
7
+ "eval_samples_per_second": 14.081,
8
+ "eval_steps_per_second": 0.886,
9
+ "eval_wer": 1.0
10
  }
evalonly_indicwav2vec_MUCS_warmup500_s300shuff100_2142198.out ADDED
@@ -0,0 +1,44 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ wandb: Currently logged in as: priyanshi-pal (priyanshipal). Use `wandb login --relogin` to force relogin
2
+ wandb: wandb version 0.17.7 is available! To upgrade, please run:
3
+ wandb: $ pip install wandb --upgrade
4
+ wandb: Tracking run with wandb version 0.17.6
5
+ wandb: Run data is saved locally in /scratch/elec/t405-puhe/p/palp3/MUCS/wandb/run-20240822_143902-r64ufk4q
6
+ wandb: Run `wandb offline` to turn off syncing.
7
+ wandb: Syncing run eval_pd2000_s300_shuff100_hindi
8
+ wandb: ⭐️ View project at https://wandb.ai/priyanshipal/huggingface
9
+ wandb: 🚀 View run at https://wandb.ai/priyanshipal/huggingface/runs/r64ufk4q
10
+ /scratch/work/palp3/myenv/lib/python3.11/site-packages/transformers/training_args.py:1525: FutureWarning: `evaluation_strategy` is deprecated and will be removed in version 4.46 of 🤗 Transformers. Use `eval_strategy` instead
11
+ warnings.warn(
12
+
13
+ Traceback (most recent call last):
14
+ File "/scratch/work/palp3/myenv/lib/python3.11/site-packages/datasets/builder.py", line 1997, in _prepare_split_single
15
+ for _, table in generator:
16
+ File "/scratch/work/palp3/myenv/lib/python3.11/site-packages/datasets/packaged_modules/json/json.py", line 98, in _generate_tables
17
+ dataset = dataset[self.config.field]
18
+ ~~~~~~~^^^^^^^^^^^^^^^^^^^
19
+ KeyError: 'test'
20
+
21
+ The above exception was the direct cause of the following exception:
22
+
23
+ Traceback (most recent call last):
24
+ File "/scratch/elec/puhe/p/palp3/MUCS/eval_script_indicwav2vec.py", line 790, in <module>
25
+ main()
26
+ File "/scratch/elec/puhe/p/palp3/MUCS/eval_script_indicwav2vec.py", line 427, in main
27
+ raw_datasets["eval"] = load_dataset(
28
+ ^^^^^^^^^^^^^
29
+ File "/scratch/work/palp3/myenv/lib/python3.11/site-packages/datasets/load.py", line 2616, in load_dataset
30
+ builder_instance.download_and_prepare(
31
+ File "/scratch/work/palp3/myenv/lib/python3.11/site-packages/datasets/builder.py", line 1029, in download_and_prepare
32
+ self._download_and_prepare(
33
+ File "/scratch/work/palp3/myenv/lib/python3.11/site-packages/datasets/builder.py", line 1124, in _download_and_prepare
34
+ self._prepare_split(split_generator, **prepare_split_kwargs)
35
+ File "/scratch/work/palp3/myenv/lib/python3.11/site-packages/datasets/builder.py", line 1884, in _prepare_split
36
+ for job_id, done, content in self._prepare_split_single(
37
+ File "/scratch/work/palp3/myenv/lib/python3.11/site-packages/datasets/builder.py", line 2040, in _prepare_split_single
38
+ raise DatasetGenerationError("An error occurred while generating the dataset") from e
39
+ datasets.exceptions.DatasetGenerationError: An error occurred while generating the dataset
40
+ wandb: - 0.005 MB of 0.005 MB uploaded
41
+ wandb: ⭐️ View project at: https://wandb.ai/priyanshipal/huggingface
42
+ wandb: Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
43
+ wandb: Find logs at: ./wandb/run-20240822_143902-r64ufk4q/logs
44
+ wandb: WARNING The new W&B backend becomes opt-out in version 0.18.0; try it out with `wandb.require("core")`! See https://wandb.me/wandb-core for more information.
evalonlyhindi_indicwav2vec_MUCS_warmup500_s300shuff100_2142336.out ADDED
@@ -0,0 +1,463 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
0
  0%| | 0/36 [00:00<?, ?it/s]
1
  6%|▌ | 2/36 [00:01<00:27, 1.23it/s]
2
  8%|▊ | 3/36 [00:02<00:34, 1.04s/it]
3
  11%|█ | 4/36 [00:04<00:42, 1.33s/it]
4
  14%|█▍ | 5/36 [00:06<00:44, 1.42s/it]
5
  17%|█▋ | 6/36 [00:07<00:42, 1.41s/it]
6
  19%|█▉ | 7/36 [00:08<00:35, 1.24s/it]
7
  22%|██▏ | 8/36 [00:09<00:27, 1.01it/s]
8
  25%|██▌ | 9/36 [00:09<00:22, 1.18it/s]
9
  28%|██▊ | 10/36 [00:10<00:21, 1.23it/s]
10
  31%|███ | 11/36 [00:11<00:20, 1.19it/s]
11
  33%|███▎ | 12/36 [00:12<00:19, 1.21it/s]
12
  36%|███▌ | 13/36 [00:12<00:18, 1.27it/s]
13
  39%|███▉ | 14/36 [00:13<00:15, 1.46it/s]
14
  42%|████▏ | 15/36 [00:13<00:12, 1.65it/s]
15
  44%|████▍ | 16/36 [00:14<00:11, 1.81it/s]
16
  47%|████▋ | 17/36 [00:14<00:09, 1.91it/s]
17
  50%|█████ | 18/36 [00:15<00:09, 1.85it/s]
18
  53%|█████▎ | 19/36 [00:15<00:09, 1.75it/s]
19
  56%|█████▌ | 20/36 [00:16<00:08, 1.81it/s]
20
  58%|█████▊ | 21/36 [00:16<00:07, 1.95it/s]
21
  61%|██████ | 22/36 [00:17<00:07, 1.96it/s]
22
  64%|██████▍ | 23/36 [00:17<00:06, 1.92it/s]
23
  67%|██████▋ | 24/36 [00:18<00:06, 1.92it/s]
24
  69%|██████▉ | 25/36 [00:18<00:06, 1.81it/s]
25
  72%|███████▏ | 26/36 [00:19<00:05, 1.84it/s]
26
  75%|███████▌ | 27/36 [00:19<00:04, 1.94it/s]
27
  78%|███████▊ | 28/36 [00:20<00:05, 1.59it/s]
28
  81%|████████ | 29/36 [00:22<00:06, 1.06it/s]
29
  83%|████████▎ | 30/36 [00:23<00:06, 1.11s/it]
30
  86%|████████▌ | 31/36 [00:25<00:06, 1.38s/it]
31
  89%|████████▉ | 32/36 [00:26<00:04, 1.15s/it]
32
  92%|█████████▏| 33/36 [00:27<00:02, 1.02it/s]
33
  94%|█████████▍| 34/36 [00:27<00:01, 1.18it/s]
34
  97%|█████████▋| 35/36 [00:28<00:00, 1.34it/s]
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ wandb: Currently logged in as: priyanshi-pal (priyanshipal). Use `wandb login --relogin` to force relogin
2
+ wandb: wandb version 0.17.7 is available! To upgrade, please run:
3
+ wandb: $ pip install wandb --upgrade
4
+ wandb: Tracking run with wandb version 0.17.6
5
+ wandb: Run data is saved locally in /scratch/elec/t405-puhe/p/palp3/MUCS/wandb/run-20240822_145052-jw39kyll
6
+ wandb: Run `wandb offline` to turn off syncing.
7
+ wandb: Syncing run eval_pd2000_s300_shuff100_hindi
8
+ wandb: ⭐️ View project at https://wandb.ai/priyanshipal/huggingface
9
+ wandb: 🚀 View run at https://wandb.ai/priyanshipal/huggingface/runs/jw39kyll
10
+ /scratch/work/palp3/myenv/lib/python3.11/site-packages/transformers/training_args.py:1525: FutureWarning: `evaluation_strategy` is deprecated and will be removed in version 4.46 of 🤗 Transformers. Use `eval_strategy` instead
11
+ warnings.warn(
12
+
13
+ /scratch/work/palp3/myenv/lib/python3.11/site-packages/transformers/models/auto/configuration_auto.py:957: FutureWarning: The `use_auth_token` argument is deprecated and will be removed in v5 of Transformers. Please use `token` instead.
14
+ warnings.warn(
15
+ /scratch/work/palp3/myenv/lib/python3.11/site-packages/transformers/configuration_utils.py:364: UserWarning: Passing `gradient_checkpointing` to a config initialization is deprecated and will be removed in v5 Transformers. Using `model.gradient_checkpointing_enable()` instead, or if you are using the `Trainer` API, pass `gradient_checkpointing=True` in your `TrainingArguments`.
16
+ warnings.warn(
17
+ /scratch/work/palp3/myenv/lib/python3.11/site-packages/transformers/models/auto/feature_extraction_auto.py:329: FutureWarning: The `use_auth_token` argument is deprecated and will be removed in v5 of Transformers. Please use `token` instead.
18
+ warnings.warn(
19
+ Wav2Vec2CTCTokenizer(name_or_path='', vocab_size=149, model_max_length=1000000000000000019884624838656, is_fast=False, padding_side='right', truncation_side='right', special_tokens={'bos_token': '<s>', 'eos_token': '</s>', 'unk_token': '[UNK]', 'pad_token': '[PAD]'}, clean_up_tokenization_spaces=True), added_tokens_decoder={
20
+ 147: AddedToken("[UNK]", rstrip=True, lstrip=True, single_word=False, normalized=False, special=False),
21
+ 148: AddedToken("[PAD]", rstrip=True, lstrip=True, single_word=False, normalized=False, special=False),
22
+ 149: AddedToken("<s>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
23
+ 150: AddedToken("</s>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
24
+ }
25
+ CHECK MODEL PARAMS Wav2Vec2ForCTC(
26
+ (wav2vec2): Wav2Vec2Model(
27
+ (feature_extractor): Wav2Vec2FeatureEncoder(
28
+ (conv_layers): ModuleList(
29
+ (0): Wav2Vec2LayerNormConvLayer(
30
+ (conv): Conv1d(1, 512, kernel_size=(10,), stride=(5,))
31
+ (layer_norm): LayerNorm((512,), eps=1e-05, elementwise_affine=True)
32
+ (activation): GELUActivation()
33
+ )
34
+ (1-4): 4 x Wav2Vec2LayerNormConvLayer(
35
+ (conv): Conv1d(512, 512, kernel_size=(3,), stride=(2,))
36
+ (layer_norm): LayerNorm((512,), eps=1e-05, elementwise_affine=True)
37
+ (activation): GELUActivation()
38
+ )
39
+ (5-6): 2 x Wav2Vec2LayerNormConvLayer(
40
+ (conv): Conv1d(512, 512, kernel_size=(2,), stride=(2,))
41
+ (layer_norm): LayerNorm((512,), eps=1e-05, elementwise_affine=True)
42
+ (activation): GELUActivation()
43
+ )
44
+ )
45
+ )
46
+ (feature_projection): Wav2Vec2FeatureProjection(
47
+ (layer_norm): LayerNorm((512,), eps=1e-05, elementwise_affine=True)
48
+ (projection): Linear(in_features=512, out_features=1024, bias=True)
49
+ (dropout): Dropout(p=0.0, inplace=False)
50
+ )
51
+ (encoder): Wav2Vec2EncoderStableLayerNorm(
52
+ (pos_conv_embed): Wav2Vec2PositionalConvEmbedding(
53
+ (conv): ParametrizedConv1d(
54
+ 1024, 1024, kernel_size=(128,), stride=(1,), padding=(64,), groups=16
55
+ (parametrizations): ModuleDict(
56
+ (weight): ParametrizationList(
57
+ (0): _WeightNorm()
58
+ )
59
+ )
60
+ )
61
+ (padding): Wav2Vec2SamePadLayer()
62
+ (activation): GELUActivation()
63
+ )
64
+ (layer_norm): LayerNorm((1024,), eps=1e-05, elementwise_affine=True)
65
+ (dropout): Dropout(p=0.0, inplace=False)
66
+ (layers): ModuleList(
67
+ (0-23): 24 x Wav2Vec2EncoderLayerStableLayerNorm(
68
+ (attention): Wav2Vec2SdpaAttention(
69
+ (k_proj): Linear(in_features=1024, out_features=1024, bias=True)
70
+ (v_proj): Linear(in_features=1024, out_features=1024, bias=True)
71
+ (q_proj): Linear(in_features=1024, out_features=1024, bias=True)
72
+ (out_proj): Linear(in_features=1024, out_features=1024, bias=True)
73
+ )
74
+ (dropout): Dropout(p=0.0, inplace=False)
75
+ (layer_norm): LayerNorm((1024,), eps=1e-05, elementwise_affine=True)
76
+ (feed_forward): Wav2Vec2FeedForward(
77
+ (intermediate_dropout): Dropout(p=0.0, inplace=False)
78
+ (intermediate_dense): Linear(in_features=1024, out_features=4096, bias=True)
79
+ (intermediate_act_fn): GELUActivation()
80
+ (output_dense): Linear(in_features=4096, out_features=1024, bias=True)
81
+ (output_dropout): Dropout(p=0.0, inplace=False)
82
+ )
83
+ (final_layer_norm): LayerNorm((1024,), eps=1e-05, elementwise_affine=True)
84
+ )
85
+ )
86
+ )
87
+ )
88
+ (dropout): Dropout(p=0.0, inplace=False)
89
+ (lm_head): Linear(in_features=1024, out_features=151, bias=True)
90
+ )
91
+
92
+ /scratch/work/palp3/myenv/lib/python3.11/site-packages/accelerate/accelerator.py:488: FutureWarning: `torch.cuda.amp.GradScaler(args...)` is deprecated. Please use `torch.amp.GradScaler('cuda', args...)` instead.
93
+ self.scaler = torch.cuda.amp.GradScaler(**kwargs)
94
+ max_steps is given, it will override any value given in num_train_epochs
95
+ 08/22/2024 14:51:18 - INFO - __main__ - *** Evaluate ***
96
+ /scratch/work/palp3/myenv/lib/python3.11/site-packages/transformers/models/wav2vec2/processing_wav2vec2.py:157: UserWarning: `as_target_processor` is deprecated and will be removed in v5 of Transformers. You can process your labels by using the argument `text` of the regular `__call__` method (either in the same call as your audio inputs, or in a separate call.
97
+ warnings.warn(
98
+
99
  0%| | 0/36 [00:00<?, ?it/s]
100
  6%|▌ | 2/36 [00:01<00:27, 1.23it/s]
101
  8%|▊ | 3/36 [00:02<00:34, 1.04s/it]
102
  11%|█ | 4/36 [00:04<00:42, 1.33s/it]
103
  14%|█▍ | 5/36 [00:06<00:44, 1.42s/it]
104
  17%|█▋ | 6/36 [00:07<00:42, 1.41s/it]
105
  19%|█▉ | 7/36 [00:08<00:35, 1.24s/it]
106
  22%|██▏ | 8/36 [00:09<00:27, 1.01it/s]
107
  25%|██▌ | 9/36 [00:09<00:22, 1.18it/s]
108
  28%|██▊ | 10/36 [00:10<00:21, 1.23it/s]
109
  31%|███ | 11/36 [00:11<00:20, 1.19it/s]
110
  33%|███▎ | 12/36 [00:12<00:19, 1.21it/s]
111
  36%|███▌ | 13/36 [00:12<00:18, 1.27it/s]
112
  39%|███▉ | 14/36 [00:13<00:15, 1.46it/s]
113
  42%|████▏ | 15/36 [00:13<00:12, 1.65it/s]
114
  44%|████▍ | 16/36 [00:14<00:11, 1.81it/s]
115
  47%|████▋ | 17/36 [00:14<00:09, 1.91it/s]
116
  50%|█████ | 18/36 [00:15<00:09, 1.85it/s]
117
  53%|█████▎ | 19/36 [00:15<00:09, 1.75it/s]
118
  56%|█████▌ | 20/36 [00:16<00:08, 1.81it/s]
119
  58%|█████▊ | 21/36 [00:16<00:07, 1.95it/s]
120
  61%|██████ | 22/36 [00:17<00:07, 1.96it/s]
121
  64%|██████▍ | 23/36 [00:17<00:06, 1.92it/s]
122
  67%|██████▋ | 24/36 [00:18<00:06, 1.92it/s]
123
  69%|██████▉ | 25/36 [00:18<00:06, 1.81it/s]
124
  72%|███████▏ | 26/36 [00:19<00:05, 1.84it/s]
125
  75%|███████▌ | 27/36 [00:19<00:04, 1.94it/s]
126
  78%|███████▊ | 28/36 [00:20<00:05, 1.59it/s]
127
  81%|████████ | 29/36 [00:22<00:06, 1.06it/s]
128
  83%|████████▎ | 30/36 [00:23<00:06, 1.11s/it]
129
  86%|████████▌ | 31/36 [00:25<00:06, 1.38s/it]
130
  89%|████████▉ | 32/36 [00:26<00:04, 1.15s/it]
131
  92%|█████████▏| 33/36 [00:27<00:02, 1.02it/s]
132
  94%|█████████▍| 34/36 [00:27<00:01, 1.18it/s]
133
  97%|█████████▋| 35/36 [00:28<00:00, 1.34it/s]
134
+ Printing predictions for a few samples:
135
+ Sample 1:
136
+ Reference: हम उनका उपयोग ऐसे ही कर सकते हैं या आवश्यकता अनुसार कुछ बदलाव करके उपयोग कर सकते हैं
137
+ ######
138
+
139
+
140
+ Prediction:
141
+
142
+
143
+
144
+ Sample 2:
145
+ Reference: अतः शीर्षक इस तरह से जोड़ सकते हैं
146
+ ######
147
+
148
+
149
+ Prediction:
150
+
151
+
152
+
153
+ Sample 3:
154
+ Reference: प्रेसेंटेशन के अंत में आपने स्लाइड की एक कॉपी बना ली है
155
+ ######
156
+
157
+
158
+ Prediction:
159
+
160
+
161
+
162
+ Sample 4:
163
+ Reference: चलिए अब फोंट्स और फोंट्स को फॉर्मेट करने के कुछ तरीके देखते हैं
164
+ ######
165
+
166
+
167
+ Prediction:
168
+
169
+
170
+
171
+ Sample 5:
172
+ Reference: यह एक डायलॉग बॉक्स खोलेगा जिसमें हम अपनी आवश्यकतानुसार फॉन्ट स्टाइल और साइज़ सेट कर सकते हैं
173
+ ######
174
+
175
+
176
+ Prediction:
177
+
178
+
179
+
180
+ last Reference string यह स्क्रिप्ट लता द्वारा अनुवादित है आईआईटी मुंबई की ओर से मैं रवि कुमार अब आपसे विदा लेता हूँहमसे जुड़ने के लिए धन्यवाद
181
+
182
+
183
+ last prediction string
184
+ ***** eval metrics *****
185
+ eval_cer = 1.0
186
+ eval_loss = nan
187
+ eval_model_preparation_time = 0.0044
188
+ eval_runtime = 0:00:40.62
189
+ eval_samples = 572
190
+ eval_samples_per_second = 14.081
191
+ eval_steps_per_second = 0.886
192
+ eval_wer = 1.0
193
+
194
+
195
+
196
+
197
+
198
+
199
+
200
+
201
+
202
+
203
+
204
+
205
+
206
+
207
+
208
+
209
+
210
+
211
+
212
+
213
+
214
+
215
+
216
+
217
+
218
+
219
+
220
+
221
+
222
+
223
+
224
+
225
+
226
+
227
+
228
+
229
+
230
+
231
+
232
+
233
+
234
+
235
+
236
+
237
+
238
+
239
+
240
+
241
+
242
+
243
+
244
+
245
+
246
+
247
+
248
+
249
+
250
+
251
+
252
+
253
+
254
+
255
+
256
+
257
+
258
+
259
+
260
+
261
+
262
+
263
+
264
+
265
+
266
+
267
+
268
+
269
+
270
+
271
+
272
+
273
+
274
+
275
+
276
+
277
+
278
+
279
+
280
+
281
+
282
+
283
+
284
+
285
+
286
+
287
+
288
+
289
+
290
+
291
+
292
+
293
+
294
+
295
+
296
+
297
+
298
+
299
+
300
+
301
+
302
+
303
+
304
+
305
+
306
+
307
+
308
+
309
+
310
+
311
+
312
+
313
+
314
+
315
+
316
+
317
+
318
+
319
+
320
+
321
+
322
+
323
+
324
+
325
+
326
+
327
+
328
+
329
+
330
+
331
+
332
+
333
+
334
+
335
+
336
+
337
+
338
+
339
+
340
+
341
+
342
+
343
+
344
+
345
+
346
+
347
+
348
+
349
+
350
+
351
+
352
+
353
+
354
+
355
+
356
+
357
+
358
+
359
+
360
+
361
+
362
+
363
+
364
+
365
+
366
+
367
+
368
+
369
+
370
+
371
+
372
+
373
+
374
+
375
+
376
+
377
+
378
+
379
+
380
+
381
+
382
+
383
+
384
+
385
+
386
+
387
+
388
+
389
+
390
+
391
+
392
+
393
+
394
+
395
+
396
+
397
+
398
+
399
+
400
+
401
+
402
+
403
+
404
+
405
+
406
+
407
+
408
+
409
+
410
+
411
+
412
+
413
+
414
+
415
+
416
+
417
+
418
+
419
+
420
+
421
+
422
+
423
+
424
+
425
+
426
+
427
+
428
+
429
+
430
+
431
+
432
+
433
+
434
+
435
+
436
+
437
+
438
+
439
+
440
+
441
+
442
+
443
+
444
+
445
+
446
+
447
+
448
+
449
+
450
+
451
+
452
+
453
+
454
+
455
+
456
+
457
+
458
+
459
+
460
+
461
+
462
+
463
+
464
+
465
+
466
+
467
+
468
+
469
+
470
+
471
+
472
+
473
+
474
+
475
+
476
+
477
+
478
+
479
+
480
+
481
+
482
+
483
+
484
+
485
+
486
+
487
+
488
+
489
+
490
+
491
+
492
+
493
+
494
+
495
+
496
+
497
+
498
+
evalonlyhinglish_indicwav2vec_MUCS_warmup500_s300shuff100_2142224.out ADDED
@@ -0,0 +1,44 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ wandb: Currently logged in as: priyanshi-pal (priyanshipal). Use `wandb login --relogin` to force relogin
2
+ wandb: wandb version 0.17.7 is available! To upgrade, please run:
3
+ wandb: $ pip install wandb --upgrade
4
+ wandb: Tracking run with wandb version 0.17.6
5
+ wandb: Run data is saved locally in /scratch/elec/t405-puhe/p/palp3/MUCS/wandb/run-20240822_144249-be92xk0e
6
+ wandb: Run `wandb offline` to turn off syncing.
7
+ wandb: Syncing run eval_pd2000_s300_shuff100_hindi
8
+ wandb: ⭐️ View project at https://wandb.ai/priyanshipal/huggingface
9
+ wandb: 🚀 View run at https://wandb.ai/priyanshipal/huggingface/runs/be92xk0e
10
+ /scratch/work/palp3/myenv/lib/python3.11/site-packages/transformers/training_args.py:1525: FutureWarning: `evaluation_strategy` is deprecated and will be removed in version 4.46 of 🤗 Transformers. Use `eval_strategy` instead
11
+ warnings.warn(
12
+
13
+ Traceback (most recent call last):
14
+ File "/scratch/work/palp3/myenv/lib/python3.11/site-packages/datasets/builder.py", line 1997, in _prepare_split_single
15
+ for _, table in generator:
16
+ File "/scratch/work/palp3/myenv/lib/python3.11/site-packages/datasets/packaged_modules/json/json.py", line 98, in _generate_tables
17
+ dataset = dataset[self.config.field]
18
+ ~~~~~~~^^^^^^^^^^^^^^^^^^^
19
+ KeyError: 'test'
20
+
21
+ The above exception was the direct cause of the following exception:
22
+
23
+ Traceback (most recent call last):
24
+ File "/scratch/elec/puhe/p/palp3/MUCS/eval_script_indicwav2vec.py", line 790, in <module>
25
+ main()
26
+ File "/scratch/elec/puhe/p/palp3/MUCS/eval_script_indicwav2vec.py", line 427, in main
27
+ raw_datasets["eval"] = load_dataset(
28
+ ^^^^^^^^^^^^^
29
+ File "/scratch/work/palp3/myenv/lib/python3.11/site-packages/datasets/load.py", line 2616, in load_dataset
30
+ builder_instance.download_and_prepare(
31
+ File "/scratch/work/palp3/myenv/lib/python3.11/site-packages/datasets/builder.py", line 1029, in download_and_prepare
32
+ self._download_and_prepare(
33
+ File "/scratch/work/palp3/myenv/lib/python3.11/site-packages/datasets/builder.py", line 1124, in _download_and_prepare
34
+ self._prepare_split(split_generator, **prepare_split_kwargs)
35
+ File "/scratch/work/palp3/myenv/lib/python3.11/site-packages/datasets/builder.py", line 1884, in _prepare_split
36
+ for job_id, done, content in self._prepare_split_single(
37
+ File "/scratch/work/palp3/myenv/lib/python3.11/site-packages/datasets/builder.py", line 2040, in _prepare_split_single
38
+ raise DatasetGenerationError("An error occurred while generating the dataset") from e
39
+ datasets.exceptions.DatasetGenerationError: An error occurred while generating the dataset
40
+ wandb: - 0.005 MB of 0.005 MB uploaded
41
+ wandb: ⭐️ View project at: https://wandb.ai/priyanshipal/huggingface
42
+ wandb: Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
43
+ wandb: Find logs at: ./wandb/run-20240822_144249-be92xk0e/logs
44
+ wandb: WARNING The new W&B backend becomes opt-out in version 0.18.0; try it out with `wandb.require("core")`! See https://wandb.me/wandb-core for more information.
indicwav2vec_MUCS_warmup500_s300shuff100_2130813.out CHANGED
@@ -1368,3 +1368,99 @@ last prediction string लता द्वारा अनुवादित ह
1368
  /scratch/work/palp3/myenv/lib/python3.11/site-packages/transformers/models/wav2vec2/processing_wav2vec2.py:157: UserWarning: `as_target_processor` is deprecated and will be removed in v5 of Transformers. You can process your labels by using the argument `text` of the regular `__call__` method (either in the same call as your audio inputs, or in a separate call.
1369
  warnings.warn(
1370
 
1371
  0%| | 0/196 [00:00<?, ?it/s]
1372
  1%| | 2/196 [00:00<01:04, 3.03it/s]
1373
  2%|▏ | 3/196 [00:01<01:31, 2.12it/s]
1374
  2%|▏ | 4/196 [00:02<01:51, 1.72it/s]
1375
  3%|▎ | 5/196 [00:02<02:05, 1.52it/s]
1376
  3%|▎ | 6/196 [00:03<02:22, 1.33it/s]
1377
  4%|▎ | 7/196 [00:04<02:25, 1.30it/s]
1378
  4%|▍ | 8/196 [00:05<02:36, 1.20it/s]
1379
  5%|▍ | 9/196 [00:07<03:28, 1.12s/it]
1380
  5%|▌ | 10/196 [00:09<04:01, 1.30s/it]
1381
  6%|▌ | 11/196 [00:10<04:34, 1.48s/it]
1382
  6%|▌ | 12/196 [00:12<04:40, 1.53s/it]
1383
  7%|▋ | 13/196 [00:13<04:02, 1.33s/it]
1384
  7%|▋ | 14/196 [00:14<03:25, 1.13s/it]
1385
  8%|▊ | 15/196 [00:14<02:54, 1.04it/s]
1386
  8%|▊ | 16/196 [00:15<02:43, 1.10it/s]
1387
  9%|▊ | 17/196 [00:16<02:43, 1.09it/s]
1388
  9%|▉ | 18/196 [00:17<03:07, 1.06s/it]
1389
  10%|▉ | 19/196 [00:19<03:56, 1.34s/it]
1390
  10%|█ | 20/196 [00:21<04:07, 1.41s/it]
1391
  11%|█ | 21/196 [00:22<04:14, 1.45s/it]
1392
  11%|█ | 22/196 [00:24<03:57, 1.37s/it]
1393
  12%|█▏ | 23/196 [00:24<03:29, 1.21s/it]
1394
  12%|█▏ | 24/196 [00:25<02:49, 1.01it/s]
1395
  13%|█▎ | 25/196 [00:25<02:27, 1.16it/s]
1396
  13%|█▎ | 26/196 [00:26<02:11, 1.29it/s]
1397
  14%|█▍ | 27/196 [00:27<02:01, 1.39it/s]
1398
  14%|█▍ | 28/196 [00:27<01:56, 1.44it/s]
1399
  15%|█▍ | 29/196 [00:28<01:57, 1.42it/s]
1400
  15%|█▌ | 30/196 [00:29<01:55, 1.44it/s]
1401
  16%|█▌ | 31/196 [00:29<01:44, 1.59it/s]
1402
  16%|█▋ | 32/196 [00:30<01:44, 1.56it/s]
1403
  17%|█▋ | 33/196 [00:31<01:59, 1.37it/s]
1404
  17%|█▋ | 34/196 [00:32<02:24, 1.12it/s]
1405
  18%|█▊ | 35/196 [00:33<02:35, 1.04it/s]
1406
  18%|█▊ | 36/196 [00:34<02:52, 1.08s/it]
1407
  19%|█▉ | 37/196 [00:35<02:46, 1.05s/it]
1408
  19%|█▉ | 38/196 [00:36<02:35, 1.02it/s]
1409
  20%|█▉ | 39/196 [00:37<02:22, 1.10it/s]
1410
  20%|██ | 40/196 [00:38<02:13, 1.17it/s]
1411
  21%|██ | 41/196 [00:38<02:02, 1.27it/s]
1412
  21%|██▏ | 42/196 [00:39<01:57, 1.31it/s]
1413
  22%|██▏ | 43/196 [00:40<01:54, 1.34it/s]
1414
  22%|██▏ | 44/196 [00:40<01:49, 1.39it/s]
1415
  23%|██▎ | 45/196 [00:41<01:43, 1.46it/s]
1416
  23%|██▎ | 46/196 [00:42<01:38, 1.53it/s]
1417
  24%|██▍ | 47/196 [00:42<01:37, 1.53it/s]
1418
  24%|██▍ | 48/196 [00:43<01:33, 1.58it/s]
1419
  25%|██▌ | 49/196 [00:44<01:32, 1.59it/s]
1420
  26%|██▌ | 50/196 [00:44<01:31, 1.60it/s]
1421
  26%|██▌ | 51/196 [00:45<01:28, 1.64it/s]
1422
  27%|██▋ | 52/196 [00:45<01:30, 1.58it/s]
1423
  27%|██▋ | 53/196 [00:46<01:30, 1.57it/s]
1424
  28%|██▊ | 54/196 [00:47<01:30, 1.57it/s]
1425
  28%|██▊ | 55/196 [00:48<01:38, 1.43it/s]
1426
  29%|██▊ | 56/196 [00:48<01:46, 1.32it/s]
1427
  29%|██▉ | 57/196 [00:49<01:51, 1.25it/s]
1428
  30%|██▉ | 58/196 [00:50<01:52, 1.23it/s]
1429
  30%|███ | 59/196 [00:51<01:49, 1.25it/s]
1430
  31%|███ | 60/196 [00:51<01:38, 1.39it/s]
1431
  31%|███ | 61/196 [00:52<01:32, 1.46it/s]
1432
  32%|███▏ | 62/196 [00:53<01:33, 1.43it/s]
1433
  32%|███▏ | 63/196 [00:54<01:34, 1.40it/s]
1434
  33%|███▎ | 64/196 [00:54<01:34, 1.40it/s]
1435
  33%|███▎ | 65/196 [00:55<01:33, 1.40it/s]
1436
  34%|███▎ | 66/196 [00:56<01:38, 1.32it/s]
1437
  34%|███▍ | 67/196 [00:57<01:40, 1.29it/s]
1438
  35%|███▍ | 68/196 [00:58<01:51, 1.15it/s]
1439
  35%|███▌ | 69/196 [00:59<01:48, 1.17it/s]
1440
  36%|███▌ | 70/196 [00:59<01:41, 1.24it/s]
1441
  36%|███▌ | 71/196 [01:00<01:34, 1.32it/s]
1442
  37%|███▋ | 72/196 [01:01<01:28, 1.39it/s]
1443
  37%|███▋ | 73/196 [01:01<01:21, 1.51it/s]
1444
  38%|███▊ | 74/196 [01:02<01:17, 1.58it/s]
1445
  38%|███▊ | 75/196 [01:02<01:15, 1.60it/s]
1446
  39%|███▉ | 76/196 [01:03<01:13, 1.63it/s]
1447
  39%|███▉ | 77/196 [01:04<01:17, 1.54it/s]
1448
  40%|███▉ | 78/196 [01:04<01:18, 1.50it/s]
1449
  40%|████ | 79/196 [01:05<01:17, 1.51it/s]
1450
  41%|████ | 80/196 [01:06<01:21, 1.42it/s]
1451
  41%|████▏ | 81/196 [01:06<01:21, 1.40it/s]
1452
  42%|████▏ | 82/196 [01:07<01:20, 1.42it/s]
1453
  42%|████▏ | 83/196 [01:08<01:22, 1.37it/s]
1454
  43%|████▎ | 84/196 [01:09<01:21, 1.37it/s]
1455
  43%|████▎ | 85/196 [01:09<01:21, 1.37it/s]
1456
  44%|████▍ | 86/196 [01:10<01:22, 1.33it/s]
1457
  44%|████▍ | 87/196 [01:11<01:21, 1.34it/s]
1458
  45%|████▍ | 88/196 [01:12<01:23, 1.29it/s]
1459
  45%|████▌ | 89/196 [01:13<01:24, 1.26it/s]
1460
  46%|████▌ | 90/196 [01:13<01:22, 1.29it/s]
1461
  46%|████▋ | 91/196 [01:14<01:17, 1.35it/s]
1462
  47%|████▋ | 92/196 [01:15<01:14, 1.40it/s]
1463
  47%|████▋ | 93/196 [01:16<01:18, 1.31it/s]
1464
  48%|████▊ | 94/196 [01:16<01:16, 1.33it/s]
1465
  48%|████▊ | 95/196 [01:17<01:15, 1.34it/s]
1466
  49%|████▉ | 96/196 [01:18<01:17, 1.28it/s]
1467
  49%|████▉ | 97/196 [01:19<01:13, 1.34it/s]
1468
  50%|█████ | 98/196 [01:19<01:14, 1.31it/s]
1469
  51%|█████ | 99/196 [01:20<01:08, 1.41it/s]
1470
  51%|█████ | 100/196 [01:20<01:00, 1.58it/s]
1471
  52%|█████▏ | 101/196 [01:21<00:58, 1.61it/s]
1472
  52%|█████▏ | 102/196 [01:22<01:02, 1.50it/s]
1473
  53%|█████▎ | 103/196 [01:23<01:08, 1.37it/s]
1474
  53%|█████▎ | 104/196 [01:24<01:15, 1.22it/s]
1475
  54%|█████▎ | 105/196 [01:24<01:15, 1.20it/s]
1476
  54%|█████▍ | 106/196 [01:25<01:13, 1.22it/s]
1477
  55%|█████▍ | 107/196 [01:26<01:08, 1.30it/s]
1478
  55%|█████▌ | 108/196 [01:26<01:00, 1.44it/s]
1479
  56%|█████▌ | 109/196 [01:27<00:57, 1.50it/s]
1480
  56%|█████▌ | 110/196 [01:28<00:56, 1.52it/s]
1481
  57%|█████▋ | 111/196 [01:28<00:56, 1.51it/s]
1482
  57%|█████▋ | 112/196 [01:29<00:57, 1.45it/s]
1483
  58%|█████▊ | 113/196 [01:30<00:56, 1.47it/s]
1484
  58%|█████▊ | 114/196 [01:30<00:52, 1.56it/s]
1485
  59%|█████▊ | 115/196 [01:31<00:51, 1.58it/s]
1486
  59%|█████▉ | 116/196 [01:32<00:50, 1.59it/s]
1487
  60%|█████▉ | 117/196 [01:32<00:46, 1.70it/s]
1488
  60%|██████ | 118/196 [01:32<00:41, 1.86it/s]
1489
  61%|██████ | 119/196 [01:33<00:44, 1.71it/s]
1490
  61%|██████ | 120/196 [01:34<00:46, 1.65it/s]
1491
  62%|██████▏ | 121/196 [01:34<00:46, 1.61it/s]
1492
  62%|██████▏ | 122/196 [01:35<00:47, 1.57it/s]
1493
  63%|██████▎ | 123/196 [01:36<00:45, 1.60it/s]
1494
  63%|██████▎ | 124/196 [01:36<00:46, 1.56it/s]
1495
  64%|██████▍ | 125/196 [01:37<00:45, 1.55it/s]
1496
  64%|██████▍ | 126/196 [01:38<00:51, 1.36it/s]
1497
  65%|██████▍ | 127/196 [01:39<00:49, 1.40it/s]
1498
  65%|██████▌ | 128/196 [01:39<00:46, 1.47it/s]
1499
  66%|██████▌ | 129/196 [01:40<00:44, 1.49it/s]
1500
  66%|██████▋ | 130/196 [01:41<00:45, 1.46it/s]
1501
  67%|██████▋ | 131/196 [01:41<00:44, 1.47it/s]
1502
  67%|██████▋ | 132/196 [01:42<00:40, 1.57it/s]
1503
  68%|██████▊ | 133/196 [01:42<00:40, 1.57it/s]
1504
  68%|██████▊ | 134/196 [01:43<00:40, 1.53it/s]
1505
  69%|██████▉ | 135/196 [01:44<00:39, 1.56it/s]
1506
  69%|██████▉ | 136/196 [01:44<00:38, 1.56it/s]
1507
  70%|██████▉ | 137/196 [01:45<00:37, 1.56it/s]
1508
  70%|███████ | 138/196 [01:46<00:36, 1.57it/s]
1509
  71%|███████ | 139/196 [01:46<00:37, 1.50it/s]
1510
  71%|███████▏ | 140/196 [01:47<00:35, 1.56it/s]
1511
  72%|███████▏ | 141/196 [01:48<00:34, 1.58it/s]
1512
  72%|███████▏ | 142/196 [01:48<00:34, 1.54it/s]
1513
  73%|███████▎ | 143/196 [01:49<00:35, 1.49it/s]
1514
  73%|███████▎ | 144/196 [01:50<00:33, 1.56it/s]
1515
  74%|███████▍ | 145/196 [01:50<00:30, 1.68it/s]
1516
  74%|███████▍ | 146/196 [01:51<00:28, 1.74it/s]
1517
  75%|███████▌ | 147/196 [01:51<00:28, 1.75it/s]
1518
  76%|███████▌ | 148/196 [01:52<00:27, 1.73it/s]
1519
  76%|███████▌ | 149/196 [01:52<00:25, 1.82it/s]
1520
  77%|███████▋ | 150/196 [01:53<00:27, 1.67it/s]
1521
  77%|███████▋ | 151/196 [01:54<00:28, 1.61it/s]
1522
  78%|███████▊ | 152/196 [01:54<00:27, 1.60it/s]
1523
  78%|███████▊ | 153/196 [01:55<00:26, 1.60it/s]
1524
  79%|███████▊ | 154/196 [01:56<00:26, 1.59it/s]
1525
  79%|███████▉ | 155/196 [01:56<00:27, 1.48it/s]
1526
  80%|███████▉ | 156/196 [01:57<00:29, 1.34it/s]
1527
  80%|████████ | 157/196 [01:58<00:30, 1.29it/s]
1528
  81%|████████ | 158/196 [01:59<00:26, 1.43it/s]
1529
  81%|████████ | 159/196 [01:59<00:24, 1.53it/s]
1530
  82%|████████▏ | 160/196 [02:00<00:23, 1.56it/s]
1531
  82%|████████▏ | 161/196 [02:00<00:22, 1.53it/s]
1532
  83%|████████▎ | 162/196 [02:01<00:21, 1.55it/s]
1533
  83%|████████▎ | 163/196 [02:02<00:20, 1.57it/s]
1534
  84%|████████▎ | 164/196 [02:02<00:20, 1.58it/s]
1535
  84%|████████▍ | 165/196 [02:03<00:20, 1.53it/s]
1536
  85%|████████▍ | 166/196 [02:04<00:19, 1.57it/s]
1537
  85%|███████���▌ | 167/196 [02:04<00:18, 1.60it/s]
1538
  86%|████████▌ | 168/196 [02:05<00:16, 1.69it/s]
1539
  86%|████████▌ | 169/196 [02:05<00:16, 1.60it/s]
1540
  87%|████████▋ | 170/196 [02:06<00:17, 1.51it/s]
1541
  87%|████████▋ | 171/196 [02:07<00:16, 1.51it/s]
1542
  88%|████████▊ | 172/196 [02:08<00:16, 1.49it/s]
1543
  88%|████████▊ | 173/196 [02:08<00:15, 1.49it/s]
1544
  89%|████████▉ | 174/196 [02:09<00:15, 1.42it/s]
1545
  89%|████████▉ | 175/196 [02:10<00:18, 1.14it/s]
1546
  90%|████████▉ | 176/196 [02:13<00:26, 1.30s/it]
1547
  90%|█████████ | 177/196 [02:14<00:28, 1.48s/it]
1548
  91%|█████████ | 178/196 [02:17<00:30, 1.67s/it]
1549
  91%|█████████▏| 179/196 [02:18<00:28, 1.66s/it]
1550
  92%|█████████▏| 180/196 [02:19<00:21, 1.37s/it]
1551
  92%|█████████▏| 181/196 [02:20<00:17, 1.16s/it]
1552
  93%|█████████▎| 182/196 [02:20<00:14, 1.01s/it]
1553
  93%|█████████▎| 183/196 [02:21<00:12, 1.01it/s]
1554
  94%|█████████▍| 184/196 [02:22<00:10, 1.13it/s]
1555
  94%|█████████▍| 185/196 [02:23<00:09, 1.17it/s]
1556
  95%|█████████▍| 186/196 [02:23<00:08, 1.17it/s]
1557
  95%|█████████▌| 187/196 [02:24<00:07, 1.26it/s]
1558
  96%|█████████▌| 188/196 [02:25<00:05, 1.34it/s]
1559
  96%|█████████▋| 189/196 [02:25<00:05, 1.38it/s]
1560
  97%|█████████▋| 190/196 [02:26<00:04, 1.45it/s]
1561
  97%|█████████▋| 191/196 [02:27<00:03, 1.52it/s]
1562
  98%|█████████▊| 192/196 [02:27<00:02, 1.49it/s]
1563
  98%|█████████▊| 193/196 [02:28<00:02, 1.48it/s]
1564
  99%|█████████▉| 194/196 [02:29<00:01, 1.51it/s]
1565
  99%|█████████▉| 195/196 [02:29<00:00, 1.56it/s]
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1368
  /scratch/work/palp3/myenv/lib/python3.11/site-packages/transformers/models/wav2vec2/processing_wav2vec2.py:157: UserWarning: `as_target_processor` is deprecated and will be removed in v5 of Transformers. You can process your labels by using the argument `text` of the regular `__call__` method (either in the same call as your audio inputs, or in a separate call.
1369
  warnings.warn(
1370
 
1371
  0%| | 0/196 [00:00<?, ?it/s]
1372
  1%| | 2/196 [00:00<01:04, 3.03it/s]
1373
  2%|▏ | 3/196 [00:01<01:31, 2.12it/s]
1374
  2%|▏ | 4/196 [00:02<01:51, 1.72it/s]
1375
  3%|▎ | 5/196 [00:02<02:05, 1.52it/s]
1376
  3%|▎ | 6/196 [00:03<02:22, 1.33it/s]
1377
  4%|▎ | 7/196 [00:04<02:25, 1.30it/s]
1378
  4%|▍ | 8/196 [00:05<02:36, 1.20it/s]
1379
  5%|▍ | 9/196 [00:07<03:28, 1.12s/it]
1380
  5%|▌ | 10/196 [00:09<04:01, 1.30s/it]
1381
  6%|▌ | 11/196 [00:10<04:34, 1.48s/it]
1382
  6%|▌ | 12/196 [00:12<04:40, 1.53s/it]
1383
  7%|▋ | 13/196 [00:13<04:02, 1.33s/it]
1384
  7%|▋ | 14/196 [00:14<03:25, 1.13s/it]
1385
  8%|▊ | 15/196 [00:14<02:54, 1.04it/s]
1386
  8%|▊ | 16/196 [00:15<02:43, 1.10it/s]
1387
  9%|▊ | 17/196 [00:16<02:43, 1.09it/s]
1388
  9%|▉ | 18/196 [00:17<03:07, 1.06s/it]
1389
  10%|▉ | 19/196 [00:19<03:56, 1.34s/it]
1390
  10%|█ | 20/196 [00:21<04:07, 1.41s/it]
1391
  11%|█ | 21/196 [00:22<04:14, 1.45s/it]
1392
  11%|█ | 22/196 [00:24<03:57, 1.37s/it]
1393
  12%|█▏ | 23/196 [00:24<03:29, 1.21s/it]
1394
  12%|█▏ | 24/196 [00:25<02:49, 1.01it/s]
1395
  13%|█▎ | 25/196 [00:25<02:27, 1.16it/s]
1396
  13%|█▎ | 26/196 [00:26<02:11, 1.29it/s]
1397
  14%|█▍ | 27/196 [00:27<02:01, 1.39it/s]
1398
  14%|█▍ | 28/196 [00:27<01:56, 1.44it/s]
1399
  15%|█▍ | 29/196 [00:28<01:57, 1.42it/s]
1400
  15%|█▌ | 30/196 [00:29<01:55, 1.44it/s]
1401
  16%|█▌ | 31/196 [00:29<01:44, 1.59it/s]
1402
  16%|█▋ | 32/196 [00:30<01:44, 1.56it/s]
1403
  17%|█▋ | 33/196 [00:31<01:59, 1.37it/s]
1404
  17%|█▋ | 34/196 [00:32<02:24, 1.12it/s]
1405
  18%|█▊ | 35/196 [00:33<02:35, 1.04it/s]
1406
  18%|█▊ | 36/196 [00:34<02:52, 1.08s/it]
1407
  19%|█▉ | 37/196 [00:35<02:46, 1.05s/it]
1408
  19%|█▉ | 38/196 [00:36<02:35, 1.02it/s]
1409
  20%|█▉ | 39/196 [00:37<02:22, 1.10it/s]
1410
  20%|██ | 40/196 [00:38<02:13, 1.17it/s]
1411
  21%|██ | 41/196 [00:38<02:02, 1.27it/s]
1412
  21%|██▏ | 42/196 [00:39<01:57, 1.31it/s]
1413
  22%|██▏ | 43/196 [00:40<01:54, 1.34it/s]
1414
  22%|██▏ | 44/196 [00:40<01:49, 1.39it/s]
1415
  23%|██▎ | 45/196 [00:41<01:43, 1.46it/s]
1416
  23%|██▎ | 46/196 [00:42<01:38, 1.53it/s]
1417
  24%|██▍ | 47/196 [00:42<01:37, 1.53it/s]
1418
  24%|██▍ | 48/196 [00:43<01:33, 1.58it/s]
1419
  25%|██▌ | 49/196 [00:44<01:32, 1.59it/s]
1420
  26%|██▌ | 50/196 [00:44<01:31, 1.60it/s]
1421
  26%|██▌ | 51/196 [00:45<01:28, 1.64it/s]
1422
  27%|██▋ | 52/196 [00:45<01:30, 1.58it/s]
1423
  27%|██▋ | 53/196 [00:46<01:30, 1.57it/s]
1424
  28%|██▊ | 54/196 [00:47<01:30, 1.57it/s]
1425
  28%|██▊ | 55/196 [00:48<01:38, 1.43it/s]
1426
  29%|██▊ | 56/196 [00:48<01:46, 1.32it/s]
1427
  29%|██▉ | 57/196 [00:49<01:51, 1.25it/s]
1428
  30%|██▉ | 58/196 [00:50<01:52, 1.23it/s]
1429
  30%|███ | 59/196 [00:51<01:49, 1.25it/s]
1430
  31%|███ | 60/196 [00:51<01:38, 1.39it/s]
1431
  31%|███ | 61/196 [00:52<01:32, 1.46it/s]
1432
  32%|███▏ | 62/196 [00:53<01:33, 1.43it/s]
1433
  32%|███▏ | 63/196 [00:54<01:34, 1.40it/s]
1434
  33%|███▎ | 64/196 [00:54<01:34, 1.40it/s]
1435
  33%|███▎ | 65/196 [00:55<01:33, 1.40it/s]
1436
  34%|███▎ | 66/196 [00:56<01:38, 1.32it/s]
1437
  34%|███▍ | 67/196 [00:57<01:40, 1.29it/s]
1438
  35%|███▍ | 68/196 [00:58<01:51, 1.15it/s]
1439
  35%|███▌ | 69/196 [00:59<01:48, 1.17it/s]
1440
  36%|███▌ | 70/196 [00:59<01:41, 1.24it/s]
1441
  36%|███▌ | 71/196 [01:00<01:34, 1.32it/s]
1442
  37%|███▋ | 72/196 [01:01<01:28, 1.39it/s]
1443
  37%|███▋ | 73/196 [01:01<01:21, 1.51it/s]
1444
  38%|███▊ | 74/196 [01:02<01:17, 1.58it/s]
1445
  38%|███▊ | 75/196 [01:02<01:15, 1.60it/s]
1446
  39%|███▉ | 76/196 [01:03<01:13, 1.63it/s]
1447
  39%|███▉ | 77/196 [01:04<01:17, 1.54it/s]
1448
  40%|███▉ | 78/196 [01:04<01:18, 1.50it/s]
1449
  40%|████ | 79/196 [01:05<01:17, 1.51it/s]
1450
  41%|████ | 80/196 [01:06<01:21, 1.42it/s]
1451
  41%|████▏ | 81/196 [01:06<01:21, 1.40it/s]
1452
  42%|████▏ | 82/196 [01:07<01:20, 1.42it/s]
1453
  42%|████▏ | 83/196 [01:08<01:22, 1.37it/s]
1454
  43%|████▎ | 84/196 [01:09<01:21, 1.37it/s]
1455
  43%|████▎ | 85/196 [01:09<01:21, 1.37it/s]
1456
  44%|████▍ | 86/196 [01:10<01:22, 1.33it/s]
1457
  44%|████▍ | 87/196 [01:11<01:21, 1.34it/s]
1458
  45%|████▍ | 88/196 [01:12<01:23, 1.29it/s]
1459
  45%|████▌ | 89/196 [01:13<01:24, 1.26it/s]
1460
  46%|████▌ | 90/196 [01:13<01:22, 1.29it/s]
1461
  46%|████▋ | 91/196 [01:14<01:17, 1.35it/s]
1462
  47%|████▋ | 92/196 [01:15<01:14, 1.40it/s]
1463
  47%|████▋ | 93/196 [01:16<01:18, 1.31it/s]
1464
  48%|████▊ | 94/196 [01:16<01:16, 1.33it/s]
1465
  48%|████▊ | 95/196 [01:17<01:15, 1.34it/s]
1466
  49%|████▉ | 96/196 [01:18<01:17, 1.28it/s]
1467
  49%|████▉ | 97/196 [01:19<01:13, 1.34it/s]
1468
  50%|█████ | 98/196 [01:19<01:14, 1.31it/s]
1469
  51%|█████ | 99/196 [01:20<01:08, 1.41it/s]
1470
  51%|█████ | 100/196 [01:20<01:00, 1.58it/s]
1471
  52%|█████▏ | 101/196 [01:21<00:58, 1.61it/s]
1472
  52%|█████▏ | 102/196 [01:22<01:02, 1.50it/s]
1473
  53%|█████▎ | 103/196 [01:23<01:08, 1.37it/s]
1474
  53%|█████▎ | 104/196 [01:24<01:15, 1.22it/s]
1475
  54%|█████▎ | 105/196 [01:24<01:15, 1.20it/s]
1476
  54%|█████▍ | 106/196 [01:25<01:13, 1.22it/s]
1477
  55%|█████▍ | 107/196 [01:26<01:08, 1.30it/s]
1478
  55%|█████▌ | 108/196 [01:26<01:00, 1.44it/s]
1479
  56%|█████▌ | 109/196 [01:27<00:57, 1.50it/s]
1480
  56%|█████▌ | 110/196 [01:28<00:56, 1.52it/s]
1481
  57%|█████▋ | 111/196 [01:28<00:56, 1.51it/s]
1482
  57%|█████▋ | 112/196 [01:29<00:57, 1.45it/s]
1483
  58%|█████▊ | 113/196 [01:30<00:56, 1.47it/s]
1484
  58%|█████▊ | 114/196 [01:30<00:52, 1.56it/s]
1485
  59%|█████▊ | 115/196 [01:31<00:51, 1.58it/s]
1486
  59%|█████▉ | 116/196 [01:32<00:50, 1.59it/s]
1487
  60%|█████▉ | 117/196 [01:32<00:46, 1.70it/s]
1488
  60%|██████ | 118/196 [01:32<00:41, 1.86it/s]
1489
  61%|██████ | 119/196 [01:33<00:44, 1.71it/s]
1490
  61%|██████ | 120/196 [01:34<00:46, 1.65it/s]
1491
  62%|██████▏ | 121/196 [01:34<00:46, 1.61it/s]
1492
  62%|██████▏ | 122/196 [01:35<00:47, 1.57it/s]
1493
  63%|██████▎ | 123/196 [01:36<00:45, 1.60it/s]
1494
  63%|██████▎ | 124/196 [01:36<00:46, 1.56it/s]
1495
  64%|██████▍ | 125/196 [01:37<00:45, 1.55it/s]
1496
  64%|██████▍ | 126/196 [01:38<00:51, 1.36it/s]
1497
  65%|██████▍ | 127/196 [01:39<00:49, 1.40it/s]
1498
  65%|██████▌ | 128/196 [01:39<00:46, 1.47it/s]
1499
  66%|██████▌ | 129/196 [01:40<00:44, 1.49it/s]
1500
  66%|██████▋ | 130/196 [01:41<00:45, 1.46it/s]
1501
  67%|██████▋ | 131/196 [01:41<00:44, 1.47it/s]
1502
  67%|██████▋ | 132/196 [01:42<00:40, 1.57it/s]
1503
  68%|██████▊ | 133/196 [01:42<00:40, 1.57it/s]
1504
  68%|██████▊ | 134/196 [01:43<00:40, 1.53it/s]
1505
  69%|██████▉ | 135/196 [01:44<00:39, 1.56it/s]
1506
  69%|██████▉ | 136/196 [01:44<00:38, 1.56it/s]
1507
  70%|██████▉ | 137/196 [01:45<00:37, 1.56it/s]
1508
  70%|███████ | 138/196 [01:46<00:36, 1.57it/s]
1509
  71%|███████ | 139/196 [01:46<00:37, 1.50it/s]
1510
  71%|███████▏ | 140/196 [01:47<00:35, 1.56it/s]
1511
  72%|███████▏ | 141/196 [01:48<00:34, 1.58it/s]
1512
  72%|███████▏ | 142/196 [01:48<00:34, 1.54it/s]
1513
  73%|███████▎ | 143/196 [01:49<00:35, 1.49it/s]
1514
  73%|███████▎ | 144/196 [01:50<00:33, 1.56it/s]
1515
  74%|███████▍ | 145/196 [01:50<00:30, 1.68it/s]
1516
  74%|███████▍ | 146/196 [01:51<00:28, 1.74it/s]
1517
  75%|███████▌ | 147/196 [01:51<00:28, 1.75it/s]
1518
  76%|███████▌ | 148/196 [01:52<00:27, 1.73it/s]
1519
  76%|███████▌ | 149/196 [01:52<00:25, 1.82it/s]
1520
  77%|███████▋ | 150/196 [01:53<00:27, 1.67it/s]
1521
  77%|███████▋ | 151/196 [01:54<00:28, 1.61it/s]
1522
  78%|███████▊ | 152/196 [01:54<00:27, 1.60it/s]
1523
  78%|███████▊ | 153/196 [01:55<00:26, 1.60it/s]
1524
  79%|███████▊ | 154/196 [01:56<00:26, 1.59it/s]
1525
  79%|███████▉ | 155/196 [01:56<00:27, 1.48it/s]
1526
  80%|███████▉ | 156/196 [01:57<00:29, 1.34it/s]
1527
  80%|████████ | 157/196 [01:58<00:30, 1.29it/s]
1528
  81%|████████ | 158/196 [01:59<00:26, 1.43it/s]
1529
  81%|████████ | 159/196 [01:59<00:24, 1.53it/s]
1530
  82%|████████▏ | 160/196 [02:00<00:23, 1.56it/s]
1531
  82%|████████▏ | 161/196 [02:00<00:22, 1.53it/s]
1532
  83%|████████▎ | 162/196 [02:01<00:21, 1.55it/s]
1533
  83%|████████▎ | 163/196 [02:02<00:20, 1.57it/s]
1534
  84%|████████▎ | 164/196 [02:02<00:20, 1.58it/s]
1535
  84%|████████▍ | 165/196 [02:03<00:20, 1.53it/s]
1536
  85%|████████▍ | 166/196 [02:04<00:19, 1.57it/s]
1537
  85%|███████���▌ | 167/196 [02:04<00:18, 1.60it/s]
1538
  86%|████████▌ | 168/196 [02:05<00:16, 1.69it/s]
1539
  86%|████████▌ | 169/196 [02:05<00:16, 1.60it/s]
1540
  87%|████████▋ | 170/196 [02:06<00:17, 1.51it/s]
1541
  87%|████████▋ | 171/196 [02:07<00:16, 1.51it/s]
1542
  88%|████████▊ | 172/196 [02:08<00:16, 1.49it/s]
1543
  88%|████████▊ | 173/196 [02:08<00:15, 1.49it/s]
1544
  89%|████████▉ | 174/196 [02:09<00:15, 1.42it/s]
1545
  89%|████████▉ | 175/196 [02:10<00:18, 1.14it/s]
1546
  90%|████████▉ | 176/196 [02:13<00:26, 1.30s/it]
1547
  90%|█████████ | 177/196 [02:14<00:28, 1.48s/it]
1548
  91%|█████████ | 178/196 [02:17<00:30, 1.67s/it]
1549
  91%|█████████▏| 179/196 [02:18<00:28, 1.66s/it]
1550
  92%|█████████▏| 180/196 [02:19<00:21, 1.37s/it]
1551
  92%|█████████▏| 181/196 [02:20<00:17, 1.16s/it]
1552
  93%|█████████▎| 182/196 [02:20<00:14, 1.01s/it]
1553
  93%|█████████▎| 183/196 [02:21<00:12, 1.01it/s]
1554
  94%|█████████▍| 184/196 [02:22<00:10, 1.13it/s]
1555
  94%|█████████▍| 185/196 [02:23<00:09, 1.17it/s]
1556
  95%|█████████▍| 186/196 [02:23<00:08, 1.17it/s]
1557
  95%|█████████▌| 187/196 [02:24<00:07, 1.26it/s]
1558
  96%|█████████▌| 188/196 [02:25<00:05, 1.34it/s]
1559
  96%|█████████▋| 189/196 [02:25<00:05, 1.38it/s]
1560
  97%|█████████▋| 190/196 [02:26<00:04, 1.45it/s]
1561
  97%|█████████▋| 191/196 [02:27<00:03, 1.52it/s]
1562
  98%|█████████▊| 192/196 [02:27<00:02, 1.49it/s]
1563
  98%|█████████▊| 193/196 [02:28<00:02, 1.48it/s]
1564
  99%|█████████▉| 194/196 [02:29<00:01, 1.51it/s]
1565
  99%|█████████▉| 195/196 [02:29<00:00, 1.56it/s]
1566
+ Printing predictions for a few samples:
1567
+ Sample 1:
1568
+ Reference: लिबर ऑफिस impress में एक प्रस्तुति document बनाना और बुनियादी formatting के इस spoken tutorial में आपका स्वागत है
1569
+ ######
1570
+
1571
+
1572
+ Prediction: liber offिc impess में एक प्रस्तुति document बनाना और बुनियादी formating के इस spoken tutorial में आपका स्वागहै
1573
+
1574
+
1575
+
1576
+ Sample 2:
1577
+ Reference: इस tutorial में हम impress window के भागों के बारे में सीखेंगे और कैसे स्लाइड इन्सर्ट करें और कॉपी करें फॉन्ट तथा फॉन्ट को फॉर्मेट करना सीखेंगे
1578
+ ######
1579
+
1580
+
1581
+ Prediction: इस tutorial में हम impres windw के भागों के बारे में सीखेंगे और कैसे slide insert करें और copy करें font तथा font को format करना सीखेंगे
1582
+
1583
+
1584
+
1585
+ Sample 3:
1586
+ Reference: यहाँ हम अपने ऑपरेटिंग सिस्टम के रूप में gnu/linux और लिबरऑफिस वर्जन 334 का उपयोग कर रहे हैं
1587
+ ######
1588
+
1589
+
1590
+ Prediction: यहाँ हम अपने operating system के रूप में gnu linuक और liber ffic version 334 का उपयोग कर रे हैं
1591
+
1592
+
1593
+
1594
+ Sample 4:
1595
+ Reference: चलिए अपनी प्रस्तुति प्रेजैटेशन sample impress open करते हैं जिसे पिछले tutorial में बनाया था
1596
+ ######
1597
+
1598
+
1599
+ Prediction: चलिए अपनी प्रस्तुति sampl impres open करते हैं जि
1600
+
1601
+
1602
+
1603
+ Sample 5:
1604
+ Reference: चलिए देखते हैं कि screen पर क्या क्या है
1605
+ ######
1606
+
1607
+
1608
+ Prediction: चलिए देखते हैं कि scren पर क्या क्या है
1609
+
1610
+
1611
+
1612
+ last Reference string यह स्क्रिप्ट लता द्वारा अनुवादित है आईआईटी मुंबई की ओर से मैं रवि कुमार अब आपसे विदा लेता हूँहमसे जुड़ने के लिए धन्यवाद
1613
+
1614
+
1615
+ last prediction string लता द्वारा अनुवादित है आई आई टी मुमं्बई की ओर से मैं रवि कुमार अब आपसे विदा लेता हूँ हमसे जुड़ने के लिए धन्यवाद
1616
+ ***** eval metrics *****
1617
+ epoch = 1.6
1618
+ eval_cer = 0.3096
1619
+ eval_loss = 1.5066
1620
+ eval_runtime = 0:02:39.31
1621
+ eval_samples = 3136
1622
+ eval_samples_per_second = 19.684
1623
+ eval_steps_per_second = 1.23
1624
+ eval_wer = 0.4357
1625
+ wandb: - 0.007 MB of 0.007 MB uploaded
1626
+ wandb: Run history:
1627
+ wandb: eval/cer ▁▁
1628
+ wandb: eval/loss ▁▁
1629
+ wandb: eval/runtime █▁
1630
+ wandb: eval/samples_per_second ▁█
1631
+ wandb: eval/steps_per_second ▁█
1632
+ wandb: eval/wer ▁▁
1633
+ wandb: train/epoch ▁▁▁▂▂▂▂▂▂▃▃▃▃▃▄▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇███
1634
+ wandb: train/global_step ▁▁▁▂▂▂▂▂▂▃▃▃▃▃▄▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇███
1635
+ wandb: train/grad_norm ▃▃█▂▇▁▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁
1636
+ wandb: train/learning_rate ▁▁▂▂▂▃▃▃▄▄▅▅▅▆▆▆▇▇▇███▇▇▇▆▆▅▅▅▄▄▄▃▃▃▂▂▁▁
1637
+ wandb: train/loss █▆▅▂▂▂▂▂▂▂▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁
1638
+ wandb:
1639
+ wandb: Run summary:
1640
+ wandb: eval/cer 0.30955
1641
+ wandb: eval/loss 1.50663
1642
+ wandb: eval/runtime 159.3193
1643
+ wandb: eval/samples_per_second 19.684
1644
+ wandb: eval/steps_per_second 1.23
1645
+ wandb: eval/wer 0.43572
1646
+ wandb: total_flos 6.212261523683712e+18
1647
+ wandb: train/epoch 1.6
1648
+ wandb: train/global_step 1000
1649
+ wandb: train/grad_norm 0.9419
1650
+ wandb: train/learning_rate 1e-05
1651
+ wandb: train/loss 0.9856
1652
+ wandb: train_loss 3.21393
1653
+ wandb: train_runtime 2133.1271
1654
+ wandb: train_samples_per_second 15.001
1655
+ wandb: train_steps_per_second 0.469
1656
+ wandb:
1657
+ wandb: 🚀 View run elated-pine-27 at: https://wandb.ai/priyanshipal/huggingface/runs/0evkescz
1658
+ wandb: ⭐️ View project at: https://wandb.ai/priyanshipal/huggingface
1659
+ wandb: Synced 6 W&B file(s), 0 media file(s), 1 artifact file(s) and 0 other file(s)
1660
+ wandb: Find logs at: ./wandb/run-20240821_155449-0evkescz/logs
1661
+ wandb: WARNING The new W&B backend becomes opt-out in version 0.18.0; try it out with `wandb.require("core")`! See https://wandb.me/wandb-core for more information.
json/default-0e1fc1524382941c/0.0.0/7483f22a71512872c377524b97484f6d20c275799bb9e7cd8fb3198178d8220a_builder.lock ADDED
File without changes
json/default-6301bb1f8040c311/0.0.0/7483f22a71512872c377524b97484f6d20c275799bb9e7cd8fb3198178d8220a_builder.lock ADDED
File without changes
json/default-b60d5edd0f197c71/0.0.0/7483f22a71512872c377524b97484f6d20c275799bb9e7cd8fb3198178d8220a.incomplete_info.lock ADDED
File without changes
json/default-b60d5edd0f197c71/0.0.0/7483f22a71512872c377524b97484f6d20c275799bb9e7cd8fb3198178d8220a/dataset_info.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"description": "", "citation": "", "homepage": "", "license": "", "features": {"audio_id": {"dtype": "string", "_type": "Value"}, "audio_paths": {"dtype": "string", "_type": "Value"}, "transcriptions": {"dtype": "string", "_type": "Value"}}, "builder_name": "json", "dataset_name": "json", "config_name": "default", "version": {"version_str": "0.0.0", "major": 0, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 159776, "num_examples": 572, "dataset_name": "json"}}, "download_checksums": {"/m/triton/scratch/elec/puhe/p/palp3/MUCS/mucs_language_segregated_data/MUCS_test_languagesep_data.json": {"num_bytes": 1275544, "checksum": null}}, "download_size": 1275544, "dataset_size": 159776, "size_in_bytes": 1435320}
json/default-b60d5edd0f197c71/0.0.0/7483f22a71512872c377524b97484f6d20c275799bb9e7cd8fb3198178d8220a/json-train.arrow ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:f67abacdef72568fdccdc70e54cc80c5aca72a7c217cf5c533dcdd9be5ca20b5
3
+ size 160568
json/default-b60d5edd0f197c71/0.0.0/7483f22a71512872c377524b97484f6d20c275799bb9e7cd8fb3198178d8220a_builder.lock ADDED
File without changes
language_segregated_prediction_texts/evalpredictions_hindi_indicw2v_ad0_3_hd_02_featd_0_2_lr6e-4_warmup500_s300_shuf100.txt ADDED
The diff for this file is too large to render. See raw diff
 
model.safetensors CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:9367c78a92aef3076de01353e7f63733eb3273ffbca6c59957741bf6a4155549
3
  size 1262426580
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:6d6e542b15e77cd1bb8a7693945d939d7b6324a0178a2a54a151c7870a9a3a70
3
  size 1262426580
training_args.bin CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:aeac58d8964b49d915038731c28a91ee0d56a3958c02bf5737260d7c08c53eba
3
  size 5432
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:fb6b542d4c167a87206ca85c8c0bf1f22fdbd339b4288aa2bc0c42cdd80202f8
3
  size 5432