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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-base |
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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 |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper Chilean Spanish Small |
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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 |
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type: Mezosky/es_clinical_assistance |
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metrics: |
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- name: Wer |
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type: wer |
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value: 204.97553017944537 |
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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 Small |
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This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the Mezosky/es_clinical_assistance dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 4.4659 |
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- Wer: 204.9755 |
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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: 1000 |
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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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| 4.6451 | 6.25 | 100 | 4.5135 | 105.7912 | |
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| 3.2485 | 12.5 | 200 | 3.3821 | 126.5905 | |
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| 2.3839 | 18.75 | 300 | 2.9779 | 215.0897 | |
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| 1.6538 | 25.0 | 400 | 3.0304 | 212.1533 | |
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| 0.887 | 31.25 | 500 | 3.4092 | 221.3703 | |
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| 0.3317 | 37.5 | 600 | 3.7754 | 191.3540 | |
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| 0.1065 | 43.75 | 700 | 4.0480 | 235.1550 | |
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| 0.0374 | 50.0 | 800 | 4.2473 | 185.4812 | |
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| 0.0173 | 56.25 | 900 | 4.4145 | 187.5204 | |
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| 0.014 | 62.5 | 1000 | 4.4659 | 204.9755 | |
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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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