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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-medium |
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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 Medium |
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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: 7.774513918030494 |
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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 Medium |
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This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) 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: 0.1058 |
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- Wer: 7.7745 |
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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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| 0.6275 | 0.17 | 100 | 0.5455 | 13.3333 | |
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| 0.185 | 0.34 | 200 | 0.1782 | 10.7316 | |
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| 0.1523 | 0.51 | 300 | 0.1539 | 10.9106 | |
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| 0.1373 | 0.69 | 400 | 0.1399 | 10.1329 | |
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| 0.1538 | 0.86 | 500 | 0.1322 | 17.5493 | |
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| 0.1007 | 1.03 | 600 | 0.1238 | 8.4963 | |
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| 0.0782 | 1.2 | 700 | 0.1187 | 8.4599 | |
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| 0.0722 | 1.37 | 800 | 0.1128 | 7.8137 | |
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| 0.0715 | 1.54 | 900 | 0.1081 | 7.6934 | |
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| 0.0927 | 1.72 | 1000 | 0.1058 | 7.7745 | |
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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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