p6_moderate / README.md
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metadata
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
  - generated_from_trainer
datasets:
  - honzapucalek/p6_moderate
metrics:
  - wer
model-index:
  - name: p6_moderate
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: honzapucalek/p6_moderate cs
          type: honzapucalek/p6_moderate
          config: cs
          split: test
          args: cs
        metrics:
          - name: Wer
            type: wer
            value: 0.2500697155605131

p6_moderate

This model is a fine-tuned version of openai/whisper-large-v3 on the honzapucalek/p6_moderate cs dataset. It achieves the following results on the evaluation set:

  • Loss: 0.8973
  • Wer: 0.2501

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: 8
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 16
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • training_steps: 5000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.0015 27.78 1000 0.7347 0.2520
0.0008 55.56 2000 0.7309 0.2523
0.0001 83.33 3000 0.8548 0.2531
0.0 111.11 4000 0.8869 0.2503
0.0 138.89 5000 0.8973 0.2501

Framework versions

  • Transformers 4.37.2
  • Pytorch 2.1.2+cu121
  • Datasets 2.16.1
  • Tokenizers 0.15.1