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whisper-large-v2.vi2

Automatic Speech Recognition
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metadata
license: apache-2.0
base_model: openai/whisper-large-v2
tags:
  - generated_from_trainer
metrics:
  - wer
model-index:
  - name: whisper-large-v2.vi2
    results: []

whisper-large-v2.vi2

This model is a fine-tuned version of openai/whisper-large-v2 on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3148
  • Wer: 13.9211

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: 250
  • training_steps: 3000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.0284 2.66 500 0.2743 21.3778
0.0047 5.32 1000 0.2707 16.1299
0.0007 7.98 1500 0.2929 12.4846
0.0004 10.64 2000 0.3040 13.3418
0.0003 13.3 2500 0.3125 13.9983
0.0003 15.96 3000 0.3148 13.9211

Framework versions

  • Transformers 4.37.2
  • Pytorch 2.1.0+cu121
  • Datasets 2.16.1
  • Tokenizers 0.15.1