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End of training
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metadata
language:
  - es
license: apache-2.0
base_model: openai/whisper-base
tags:
  - generated_from_trainer
datasets:
  - Mezosky/es_clinical_assistance
metrics:
  - wer
model-index:
  - name: Whisper Chilean Spanish Small
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Mezosky/es_clinical_assistance
          type: Mezosky/es_clinical_assistance
        metrics:
          - name: Wer
            type: wer
            value: 204.97553017944537

Whisper Chilean Spanish Small

This model is a fine-tuned version of openai/whisper-base on the Mezosky/es_clinical_assistance dataset. It achieves the following results on the evaluation set:

  • Loss: 4.4659
  • Wer: 204.9755

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 1e-05
  • train_batch_size: 16
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • training_steps: 1000

Training results

Training Loss Epoch Step Validation Loss Wer
4.6451 6.25 100 4.5135 105.7912
3.2485 12.5 200 3.3821 126.5905
2.3839 18.75 300 2.9779 215.0897
1.6538 25.0 400 3.0304 212.1533
0.887 31.25 500 3.4092 221.3703
0.3317 37.5 600 3.7754 191.3540
0.1065 43.75 700 4.0480 235.1550
0.0374 50.0 800 4.2473 185.4812
0.0173 56.25 900 4.4145 187.5204
0.014 62.5 1000 4.4659 204.9755

Framework versions

  • Transformers 4.39.3
  • Pytorch 2.2.2+cu121
  • Datasets 2.18.0
  • Tokenizers 0.15.2