whisper-ckm-8 / README.md
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metadata
language:
  - cr
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
  - generated_from_trainer
datasets:
  - audiofolder
metrics:
  - wer
model-index:
  - name: whisper-large-v3-croarian_overlap_removed_20
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: audiofolder
          type: audiofolder
          config: default
          split: train
          args: 'config: cr, split: test'
        metrics:
          - name: Wer
            type: wer
            value: 66.4162460382674

whisper-large-v3-croarian_overlap_removed_20

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

  • Loss: 2.1494
  • Wer: 66.4162

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: 4000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.0196 18.18 1000 1.8624 74.2693
0.0034 36.36 2000 2.0306 57.5067
0.0028 54.55 3000 2.1057 61.0400
0.0029 72.73 4000 2.1494 66.4162

Framework versions

  • Transformers 4.37.1
  • Pytorch 2.2.1+cu121
  • Datasets 2.18.0
  • Tokenizers 0.15.1