Model save

.gitattributes

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 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+wandb/run-20240122_192258-yf2elmz6/run-yf2elmz6.wandb filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,78 @@
+---
+license: apache-2.0
+base_model: openai/whisper-large-v3
+tags:
+- generated_from_trainer
+datasets:
+- common_voice_16_0
+metrics:
+- wer
+model-index:
+- name: openai/whisper-large-v3
+  results:
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: common_voice_16_0
+      type: common_voice_16_0
+      config: mn
+      split: test
+      args: mn
+    metrics:
+    - name: Wer
+      type: wer
+      value: 41.048913043478265
+---
+
+<!-- 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. -->
+
+# openai/whisper-large-v3
+
+This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the common_voice_16_0 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5425
+- Wer: 41.0489
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 0.0001
+- train_batch_size: 32
+- eval_batch_size: 32
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 500
+- num_epochs: 10.0
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Wer     |
+|:-------------:|:-----:|:----:|:---------------:|:-------:|
+| 0.1378        | 4.35  | 500  | 0.5576          | 51.2554 |
+| 0.0024        | 8.7   | 1000 | 0.5425          | 41.0489 |
+
+
+### Framework versions
+
+- Transformers 4.38.0.dev0
+- Pytorch 2.1.2+cu121
+- Datasets 2.16.2.dev0
+- Tokenizers 0.15.0

generation_config.json

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wandb/run-20240122_192258-yf2elmz6/files/config.yaml

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wandb/run-20240122_192258-yf2elmz6/files/output.log

@@ -1025,3 +1025,172 @@ Non-default generation parameters: {'max_length': 448, 'begin_suppress_tokens':
 [INFO|configuration_utils.py:595] 2024-01-22 20:18:14,572 >> Configuration saved in ./tmp-checkpoint-1000/generation_config.json
 {'eval_loss': 0.5424743294715881, 'eval_wer': 41.048913043478265, 'eval_runtime': 781.806, 'eval_samples_per_second': 2.421, 'eval_steps_per_second': 0.077, 'epoch': 8.7}
 [INFO|modeling_utils.py:2503] 2024-01-22 20:18:29,139 >> The model is bigger than the maximum size per checkpoint (5GB) and is going to be split in 2 checkpoint shards. You can find where each parameters has been saved in the index located at ./tmp-checkpoint-1000/model.safetensors.index.json.
+[INFO|feature_extraction_utils.py:425] 2024-01-22 20:18:29,140 >> Feature extractor saved in ./tmp-checkpoint-1000/preprocessor_config.json
+[INFO|feature_extraction_utils.py:425] 2024-01-22 20:18:46,797 >> Feature extractor saved in ./preprocessor_config.json
+/home/sanchit/hf/lib/python3.8/site-packages/torch/utils/checkpoint.py:429: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.
+  warnings.warn(
+/home/sanchit/hf/lib/python3.8/site-packages/torch/utils/checkpoint.py:61: UserWarning: None of the inputs have requires_grad=True. Gradients will be None
+  warnings.warn(
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+{'loss': 0.0008, 'learning_rate': 0.0, 'epoch': 10.0}
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+Training completed. Do not forget to share your model on huggingface.co/models =)
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+[INFO|trainer.py:2926] 2024-01-22 20:23:33,137 >> Saving model checkpoint to ./
+[WARNING|configuration_utils.py:449] 2024-01-22 20:23:33,137 >> Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.
+Non-default generation parameters: {'max_length': 448, 'begin_suppress_tokens': [220, 50257]}
+[INFO|configuration_utils.py:473] 2024-01-22 20:23:33,138 >> Configuration saved in ./config.json
+[INFO|configuration_utils.py:595] 2024-01-22 20:23:33,138 >> Configuration saved in ./generation_config.json
+[INFO|modeling_utils.py:2503] 2024-01-22 20:23:45,892 >> The model is bigger than the maximum size per checkpoint (5GB) and is going to be split in 2 checkpoint shards. You can find where each parameters has been saved in the index located at ./model.safetensors.index.json.
+[INFO|feature_extraction_utils.py:425] 2024-01-22 20:23:45,893 >> Feature extractor saved in ./preprocessor_config.json
+[INFO|trainer.py:2926] 2024-01-22 20:23:45,894 >> Saving model checkpoint to ./
+[WARNING|configuration_utils.py:449] 2024-01-22 20:23:45,894 >> Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.
+Non-default generation parameters: {'max_length': 448, 'begin_suppress_tokens': [220, 50257]}
+[INFO|configuration_utils.py:473] 2024-01-22 20:23:45,895 >> Configuration saved in ./config.json
+[INFO|configuration_utils.py:595] 2024-01-22 20:23:45,895 >> Configuration saved in ./generation_config.json
+[INFO|modeling_utils.py:2503] 2024-01-22 20:24:01,028 >> The model is bigger than the maximum size per checkpoint (5GB) and is going to be split in 2 checkpoint shards. You can find where each parameters has been saved in the index located at ./model.safetensors.index.json.
+[INFO|feature_extraction_utils.py:425] 2024-01-22 20:24:01,030 >> Feature extractor saved in ./preprocessor_config.json
+events.out.tfevents.1705947776.hf-dgx-01.122884.0: 100%|███████████████████████████| 13.3k/13.3k [00:00<00:00, 95.8kB/s]
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+model-00001-of-00002.safetensors:   1%|▎                                           | 29.1M/4.99G [00:01<02:52, 28.7MB/s]
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