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--- |
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language: |
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- en |
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license: apache-2.0 |
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base_model: openai/whisper-base |
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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: openai/whisper-base |
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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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# openai/whisper-base |
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This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the pphuc25/EngMed dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.3225 |
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- Wer: 27.9808 |
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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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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.0001 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 100 |
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- num_epochs: 20 |
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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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| 0.7862 | 1.0 | 3491 | 0.8811 | 43.2441 | |
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| 0.5443 | 2.0 | 6982 | 0.8834 | 38.7694 | |
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| 0.3319 | 3.0 | 10473 | 0.9247 | 34.6764 | |
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| 0.2412 | 4.0 | 13964 | 0.9765 | 34.9636 | |
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| 0.1809 | 5.0 | 17455 | 1.0223 | 31.3646 | |
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| 0.1112 | 6.0 | 20946 | 1.1013 | 33.5169 | |
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| 0.0786 | 7.0 | 24437 | 1.1217 | 34.1563 | |
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| 0.0666 | 8.0 | 27928 | 1.1698 | 36.5356 | |
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| 0.0487 | 9.0 | 31419 | 1.1934 | 33.9412 | |
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| 0.0395 | 10.0 | 34910 | 1.2259 | 31.4509 | |
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| 0.0229 | 11.0 | 38401 | 1.2614 | 32.0655 | |
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| 0.0181 | 12.0 | 41892 | 1.2823 | 30.5444 | |
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| 0.0118 | 13.0 | 45383 | 1.2890 | 30.2773 | |
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| 0.0069 | 14.0 | 48874 | 1.3081 | 30.3435 | |
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| 0.0073 | 15.0 | 52365 | 1.3085 | 30.4097 | |
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| 0.0017 | 16.0 | 55856 | 1.3099 | 29.4145 | |
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| 0.0062 | 17.0 | 59347 | 1.3229 | 29.5386 | |
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| 0.0013 | 18.0 | 62838 | 1.3162 | 28.3058 | |
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| 0.0001 | 19.0 | 66329 | 1.3197 | 28.0387 | |
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| 0.0001 | 20.0 | 69820 | 1.3225 | 27.9808 | |
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### Framework versions |
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- Transformers 4.41.1 |
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- Pytorch 2.3.0 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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