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--- |
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language: |
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- es |
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license: apache-2.0 |
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base_model: openai/whisper-large-v3 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- Mezosky/es_clinical_assistance_10k |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper Chilean Spanish Large v3 |
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results: |
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- task: |
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name: Automatic Speech Recognition |
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type: automatic-speech-recognition |
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dataset: |
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name: Mezosky/es_clinical_assistance_10k |
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type: Mezosky/es_clinical_assistance_10k |
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metrics: |
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- name: Wer |
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type: wer |
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value: 6.935235697300322 |
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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 Chilean Spanish Large v3 |
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This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co./openai/whisper-large-v3) on the Mezosky/es_clinical_assistance_10k dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0961 |
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- Wer: 6.9352 |
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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: 1e-05 |
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- train_batch_size: 16 |
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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: 500 |
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- training_steps: 2000 |
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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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| 0.2816 | 0.17 | 100 | 0.2250 | 11.2827 | |
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| 0.1505 | 0.34 | 200 | 0.1479 | 9.8196 | |
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| 0.1293 | 0.51 | 300 | 0.1350 | 72.1192 | |
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| 0.1221 | 0.69 | 400 | 0.1292 | 9.6825 | |
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| 0.141 | 0.86 | 500 | 0.1194 | 53.0899 | |
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| 0.0922 | 1.03 | 600 | 0.1150 | 12.0380 | |
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| 0.0773 | 1.2 | 700 | 0.1079 | 12.8661 | |
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| 0.0745 | 1.37 | 800 | 0.1036 | 67.3017 | |
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| 0.0699 | 1.54 | 900 | 0.1016 | 8.2697 | |
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| 0.0917 | 1.72 | 1000 | 0.0956 | 8.6334 | |
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| 0.0716 | 1.89 | 1100 | 0.0968 | 7.7997 | |
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| 0.0441 | 2.06 | 1200 | 0.0946 | 8.3760 | |
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| 0.0377 | 2.23 | 1300 | 0.0963 | 7.6178 | |
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| 0.0417 | 2.4 | 1400 | 0.0951 | 7.5703 | |
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| 0.0409 | 2.57 | 1500 | 0.0926 | 7.2681 | |
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| 0.0356 | 2.74 | 1600 | 0.0912 | 6.8933 | |
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| 0.0361 | 2.92 | 1700 | 0.0918 | 7.0835 | |
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| 0.0215 | 3.09 | 1800 | 0.0938 | 6.9548 | |
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| 0.018 | 3.26 | 1900 | 0.0960 | 6.6415 | |
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| 0.0196 | 3.43 | 2000 | 0.0961 | 6.9352 | |
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### Framework versions |
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- Transformers 4.39.3 |
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- Pytorch 2.2.2+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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