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--- |
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license: apache-2.0 |
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base_model: openai/whisper-tiny |
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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: torgo_tiny_finetune_M01 |
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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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# torgo_tiny_finetune_M01 |
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This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3526 |
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- Wer: 96.6044 |
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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: 16 |
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- eval_batch_size: 1 |
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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: 1000 |
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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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| 0.6272 | 0.85 | 500 | 0.2872 | 24.1087 | |
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| 0.1055 | 1.7 | 1000 | 0.3364 | 77.5042 | |
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| 0.0998 | 2.55 | 1500 | 0.3646 | 65.8744 | |
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| 0.0635 | 3.4 | 2000 | 0.3276 | 34.9745 | |
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| 0.0521 | 4.24 | 2500 | 0.3619 | 31.8336 | |
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| 0.0368 | 5.09 | 3000 | 0.3158 | 43.0390 | |
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| 0.0269 | 5.94 | 3500 | 0.3424 | 53.7351 | |
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| 0.0215 | 6.79 | 4000 | 0.2886 | 48.8964 | |
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| 0.0182 | 7.64 | 4500 | 0.3331 | 31.0696 | |
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| 0.0135 | 8.49 | 5000 | 0.3308 | 45.0764 | |
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| 0.0092 | 9.34 | 5500 | 0.2825 | 28.9474 | |
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| 0.0088 | 10.19 | 6000 | 0.3169 | 32.3430 | |
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| 0.0056 | 11.04 | 6500 | 0.3223 | 55.7725 | |
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| 0.0034 | 11.88 | 7000 | 0.3396 | 30.2207 | |
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| 0.0041 | 12.73 | 7500 | 0.3403 | 31.8336 | |
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| 0.0031 | 13.58 | 8000 | 0.3544 | 138.4550 | |
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| 0.0023 | 14.43 | 8500 | 0.3357 | 54.8387 | |
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| 0.0004 | 15.28 | 9000 | 0.3618 | 53.6503 | |
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| 0.0003 | 16.13 | 9500 | 0.3598 | 74.3633 | |
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| 0.0002 | 16.98 | 10000 | 0.3536 | 98.8964 | |
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| 0.0003 | 17.83 | 10500 | 0.3529 | 95.8404 | |
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| 0.0001 | 18.68 | 11000 | 0.3505 | 98.0475 | |
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| 0.0001 | 19.52 | 11500 | 0.3526 | 96.6044 | |
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### Framework versions |
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- Transformers 4.32.0 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.14.7 |
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- Tokenizers 0.13.3 |
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