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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: openai/whisper-medium.en |
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tags: |
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- generated_from_trainer |
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metrics: |
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- wer |
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model-index: |
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- name: whisper-medium.en |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# whisper-medium.en |
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This model is a fine-tuned version of [openai/whisper-medium.en](https://huggingface.co/openai/whisper-medium.en) on an [acc_dataset_v3](https://huggingface.co/datasets/monadical-labs/acc_dataset_v3) dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4242 |
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- Wer: 0.1293 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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See the training notebook [here](https://huggingface.co/monadical-labs/whisper-medium.en/blob/main/Finetuning-notebook-whisper-on-acc-data.ipynb): |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 25 |
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- training_steps: 300 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Wer | |
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|:-------------:|:-------:|:----:|:---------------:|:------:| |
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| 1.6045 | 2.2727 | 25 | 0.9047 | 0.1535 | |
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| 0.2267 | 4.5455 | 50 | 0.4149 | 0.1262 | |
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| 0.0207 | 6.8182 | 75 | 0.4454 | 0.1483 | |
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| 0.0134 | 9.0909 | 100 | 0.4660 | 0.1388 | |
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| 0.009 | 11.3636 | 125 | 0.4311 | 0.1462 | |
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| 0.0051 | 13.6364 | 150 | 0.4368 | 0.1356 | |
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| 0.0018 | 15.9091 | 175 | 0.4294 | 0.1462 | |
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| 0.0003 | 18.1818 | 200 | 0.4234 | 0.1356 | |
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| 0.0002 | 20.4545 | 225 | 0.4235 | 0.1325 | |
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| 0.0002 | 22.7273 | 250 | 0.4239 | 0.1304 | |
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| 0.0002 | 25.0 | 275 | 0.4240 | 0.1283 | |
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| 0.0002 | 27.2727 | 300 | 0.4242 | 0.1293 | |
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### Framework versions |
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- Transformers 4.48.2 |
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- Pytorch 2.6.0+cu124 |
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- Datasets 3.2.0 |
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- Tokenizers 0.21.0 |
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