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End of training
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metadata
language:
  - es
license: apache-2.0
base_model: openai/whisper-medium
tags:
  - generated_from_trainer
datasets:
  - Mezosky/es_clinical_assistance_10k
metrics:
  - wer
model-index:
  - name: Whisper Chilean Spanish Medium
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Mezosky/es_clinical_assistance_10k
          type: Mezosky/es_clinical_assistance_10k
        metrics:
          - name: Wer
            type: wer
            value: 7.774513918030494

Whisper Chilean Spanish Medium

This model is a fine-tuned version of openai/whisper-medium on the Mezosky/es_clinical_assistance_10k dataset. It achieves the following results on the evaluation set:

  • Loss: 0.1058
  • Wer: 7.7745

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
0.6275 0.17 100 0.5455 13.3333
0.185 0.34 200 0.1782 10.7316
0.1523 0.51 300 0.1539 10.9106
0.1373 0.69 400 0.1399 10.1329
0.1538 0.86 500 0.1322 17.5493
0.1007 1.03 600 0.1238 8.4963
0.0782 1.2 700 0.1187 8.4599
0.0722 1.37 800 0.1128 7.8137
0.0715 1.54 900 0.1081 7.6934
0.0927 1.72 1000 0.1058 7.7745

Framework versions

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