End of training

README.md

@@ -9,18 +9,18 @@ model-index:
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 should probably proofread and complete it, then remove this comment. -->
 
-[<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)
+[<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/1kodfy70)
 # s300_shuff100
 
 This model was trained from scratch on an unknown dataset.
 It achieves the following results on the evaluation set:
 - eval_loss: nan
-- eval_model_preparation_time: 0.0044
+- eval_model_preparation_time: 0.0046
 - eval_cer: 1.0
 - eval_wer: 1.0
-- eval_runtime: 40.6214
-- eval_samples_per_second: 14.081
-- eval_steps_per_second: 0.886
+- eval_runtime: 39.8895
+- eval_samples_per_second: 14.34
+- eval_steps_per_second: 0.902
 - step: 0
 
 ## Model description

all_results.json

@@ -2,11 +2,11 @@
     "epoch": 1.6,
     "eval_cer": 1.0,
     "eval_loss": NaN,
-    "eval_model_preparation_time": 0.0044,
-    "eval_runtime": 40.6214,
+    "eval_model_preparation_time": 0.0046,
+    "eval_runtime": 39.8895,
     "eval_samples": 572,
-    "eval_samples_per_second": 14.081,
-    "eval_steps_per_second": 0.886,
+    "eval_samples_per_second": 14.34,
+    "eval_steps_per_second": 0.902,
     "eval_wer": 1.0,
     "total_flos": 6.212261523683712e+18,
     "train_loss": 3.21392811447382,

config.json

@@ -1,5 +1,5 @@
 {
-  "_name_or_path": "/m/triton/scratch/elec/puhe/p/palp3/MUCS/indicwav2vec-hindi",
+  "_name_or_path": "/scratch/elec/puhe/p/palp3/MUCS/indicwav2vec_outputs/pd_warmup_500/s300_shuff100",
   "activation_dropout": 0.0,
   "adapter_attn_dim": null,
   "adapter_kernel_size": 3,

eval_results.json

@@ -1,10 +1,10 @@
 {
     "eval_cer": 1.0,
     "eval_loss": NaN,
-    "eval_model_preparation_time": 0.0044,
-    "eval_runtime": 40.6214,
+    "eval_model_preparation_time": 0.0046,
+    "eval_runtime": 39.8895,
     "eval_samples": 572,
-    "eval_samples_per_second": 14.081,
-    "eval_steps_per_second": 0.886,
+    "eval_samples_per_second": 14.34,
+    "eval_steps_per_second": 0.902,
     "eval_wer": 1.0
 }

evalonlyhindi_indicwav2vec_MUCS_warmup500_s300shuff100_2142336.out

@@ -461,3 +461,43 @@ last prediction string
 
 
 
+wandb: - 0.007 MB of 0.007 MB uploaded
+wandb: Run history:
+wandb:                    eval/cer ▁
+wandb: eval/model_preparation_time ▁
+wandb:                eval/runtime ▁
+wandb:     eval/samples_per_second ▁
+wandb:       eval/steps_per_second ▁
+wandb:                    eval/wer ▁
+wandb:                    eval_cer ▁
+wandb: eval_model_preparation_time ▁
+wandb:                eval_runtime ▁
+wandb:                eval_samples ▁
+wandb:     eval_samples_per_second ▁
+wandb:       eval_steps_per_second ▁
+wandb:                    eval_wer ▁
+wandb:           train/global_step ▁▁
+wandb: 
+wandb: Run summary:
+wandb:                    eval/cer 1.0
+wandb:                   eval/loss nan
+wandb: eval/model_preparation_time 0.0044
+wandb:                eval/runtime 40.6214
+wandb:     eval/samples_per_second 14.081
+wandb:       eval/steps_per_second 0.886
+wandb:                    eval/wer 1.0
+wandb:                    eval_cer 1.0
+wandb:                   eval_loss nan
+wandb: eval_model_preparation_time 0.0044
+wandb:                eval_runtime 40.6214
+wandb:                eval_samples 572
+wandb:     eval_samples_per_second 14.081
+wandb:       eval_steps_per_second 0.886
+wandb:                    eval_wer 1.0
+wandb:           train/global_step 0
+wandb: 
+wandb: 🚀 View run eval_pd2000_s300_shuff100_hindi at: https://wandb.ai/priyanshipal/huggingface/runs/jw39kyll
+wandb: ⭐️ View project at: https://wandb.ai/priyanshipal/huggingface
+wandb: Synced 6 W&B file(s), 0 media file(s), 1 artifact file(s) and 0 other file(s)
+wandb: Find logs at: ./wandb/run-20240822_145052-jw39kyll/logs
+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_2142383.out

@@ -0,0 +1,154 @@
+wandb: Currently logged in as: priyanshi-pal (priyanshipal). Use `wandb login --relogin` to force relogin
+wandb: wandb version 0.17.7 is available!  To upgrade, please run:
+wandb:  $ pip install wandb --upgrade
+wandb: Tracking run with wandb version 0.17.6
+wandb: Run data is saved locally in /scratch/elec/t405-puhe/p/palp3/MUCS/wandb/run-20240822_150154-1kodfy70
+wandb: Run `wandb offline` to turn off syncing.
+wandb: Syncing run eval_pd2000_s300_shuff100_hindi
+wandb: ⭐️ View project at https://wandb.ai/priyanshipal/huggingface
+wandb: 🚀 View run at https://wandb.ai/priyanshipal/huggingface/runs/1kodfy70
+/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
+  warnings.warn(
+/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.
+  warnings.warn(
+/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.
+  warnings.warn(
+/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.
+  self.scaler = torch.cuda.amp.GradScaler(**kwargs)
+max_steps is given, it will override any value given in num_train_epochs
+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={
+	147: AddedToken("[UNK]", rstrip=True, lstrip=True, single_word=False, normalized=False, special=False),
+	148: AddedToken("[PAD]", rstrip=True, lstrip=True, single_word=False, normalized=False, special=False),
+	149: AddedToken("<s>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
+	150: AddedToken("</s>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
+}
+CHECK MODEL PARAMS Wav2Vec2ForCTC(
+  (wav2vec2): Wav2Vec2Model(
+    (feature_extractor): Wav2Vec2FeatureEncoder(
+      (conv_layers): ModuleList(
+        (0): Wav2Vec2LayerNormConvLayer(
+          (conv): Conv1d(1, 512, kernel_size=(10,), stride=(5,))
+          (layer_norm): LayerNorm((512,), eps=1e-05, elementwise_affine=True)
+          (activation): GELUActivation()
+        )
+        (1-4): 4 x Wav2Vec2LayerNormConvLayer(
+          (conv): Conv1d(512, 512, kernel_size=(3,), stride=(2,))
+          (layer_norm): LayerNorm((512,), eps=1e-05, elementwise_affine=True)
+          (activation): GELUActivation()
+        )
+        (5-6): 2 x Wav2Vec2LayerNormConvLayer(
+          (conv): Conv1d(512, 512, kernel_size=(2,), stride=(2,))
+          (layer_norm): LayerNorm((512,), eps=1e-05, elementwise_affine=True)
+          (activation): GELUActivation()
+        )
+      )
+    )
+    (feature_projection): Wav2Vec2FeatureProjection(
+      (layer_norm): LayerNorm((512,), eps=1e-05, elementwise_affine=True)
+      (projection): Linear(in_features=512, out_features=1024, bias=True)
+      (dropout): Dropout(p=0.0, inplace=False)
+    )
+    (encoder): Wav2Vec2EncoderStableLayerNorm(
+      (pos_conv_embed): Wav2Vec2PositionalConvEmbedding(
+        (conv): ParametrizedConv1d(
+          1024, 1024, kernel_size=(128,), stride=(1,), padding=(64,), groups=16
+          (parametrizations): ModuleDict(
+            (weight): ParametrizationList(
+              (0): _WeightNorm()
+            )
+          )
+        )
+        (padding): Wav2Vec2SamePadLayer()
+        (activation): GELUActivation()
+      )
+      (layer_norm): LayerNorm((1024,), eps=1e-05, elementwise_affine=True)
+      (dropout): Dropout(p=0.0, inplace=False)
+      (layers): ModuleList(
+        (0-23): 24 x Wav2Vec2EncoderLayerStableLayerNorm(
+          (attention): Wav2Vec2SdpaAttention(
+            (k_proj): Linear(in_features=1024, out_features=1024, bias=True)
+            (v_proj): Linear(in_features=1024, out_features=1024, bias=True)
+            (q_proj): Linear(in_features=1024, out_features=1024, bias=True)
+            (out_proj): Linear(in_features=1024, out_features=1024, bias=True)
+          )
+          (dropout): Dropout(p=0.0, inplace=False)
+          (layer_norm): LayerNorm((1024,), eps=1e-05, elementwise_affine=True)
+          (feed_forward): Wav2Vec2FeedForward(
+            (intermediate_dropout): Dropout(p=0.0, inplace=False)
+            (intermediate_dense): Linear(in_features=1024, out_features=4096, bias=True)
+            (intermediate_act_fn): GELUActivation()
+            (output_dense): Linear(in_features=4096, out_features=1024, bias=True)
+            (output_dropout): Dropout(p=0.0, inplace=False)
+          )
+          (final_layer_norm): LayerNorm((1024,), eps=1e-05, elementwise_affine=True)
+        )
+      )
+    )
+  )
+  (dropout): Dropout(p=0.0, inplace=False)
+  (lm_head): Linear(in_features=1024, out_features=151, bias=True)
+)
+08/22/2024 15:02:06 - INFO - __main__ - *** Evaluate ***
+/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.
+  warnings.warn(
+
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+Printing predictions for a few samples:
+Sample 1:
+  Reference: हम उनका उपयोग ऐसे ही कर सकते हैं या आवश्यकता अनुसार कुछ बदलाव करके उपयोग कर सकते हैं
+######
+
+
+  Prediction: 
+
+
+
+Sample 2:
+  Reference: अतः शीर्षक इस तरह से जोड़ सकते हैं
+######
+
+
+  Prediction: 
+
+
+
+Sample 3:
+  Reference: प्रेसेंटेशन के अंत में आपने स्लाइड की एक कॉपी बना ली है
+######
+
+
+  Prediction: 
+
+
+
+Sample 4:
+  Reference: चलिए अब फोंट्स और फोंट्स को फॉर्मेट करने के कुछ तरीके देखते हैं
+######
+
+
+  Prediction: 
+
+
+
+Sample 5:
+  Reference: यह एक डायलॉग बॉक्स खोलेगा जिसमें हम अपनी आवश्यकतानुसार फॉन्ट स्टाइल और साइज़ सेट कर सकते हैं
+######
+
+
+  Prediction: 
+
+
+
+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
+
+
+last prediction string 
+***** eval metrics *****
+  eval_cer                    =        1.0
+  eval_loss                   =        nan
+  eval_model_preparation_time =     0.0046
+  eval_runtime                = 0:00:39.88
+  eval_samples                =        572
+  eval_samples_per_second     =      14.34
+  eval_steps_per_second       =      0.902
+  eval_wer                    =        1.0
+

training_args.bin

@@ -1,3 +1,3 @@
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+oid sha256:2ac994ec93d9297038ccd8f0941bd5189ab98d5a22407edafc2b896159805ce1
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