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metadata
language:
  - vi
license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_11_0
metrics:
  - wer
base_model: openai/whisper-large-v2
model-index:
  - name: openai/whisper-large-v2
    results:
      - task:
          type: automatic-speech-recognition
          name: Automatic Speech Recognition
        dataset:
          name: mozilla-foundation/common_voice_11_0 vi
          type: mozilla-foundation/common_voice_11_0
          config: vi
          split: test
          args: vi
        metrics:
          - type: wer
            value: 15.771
            name: Wer
          - type: cer
            value: 7.6691
            name: Cer

openai/whisper-large-v2

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: 0.4041
  • Wer: 15.7710
  • Cer: 7.6691

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

Training data:

Evaluation data:

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 1e-07
  • train_batch_size: 8
  • eval_batch_size: 4
  • seed: 42
  • gradient_accumulation_steps: 3
  • total_train_batch_size: 24
  • 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 Cer
0.3983 0.1 500 0.5338 19.5876 10.6391
0.2277 1.08 1000 0.4134 16.5826 8.2668
0.172 2.05 1500 0.3968 16.3084 7.9787
0.1823 3.03 2000 0.3956 16.1768 7.8159
0.1445 4.0 2500 0.3955 16.0342 7.7438
0.147 4.1 3000 0.3965 15.8807 7.7145
0.1292 5.08 3500 0.4000 15.8587 7.7065
0.1187 6.05 4000 0.4029 15.7491 7.6398
0.1368 7.03 4500 0.4041 15.7600 7.6558
0.1231 8.0 5000 0.4041 15.7710 7.6691

Framework versions

  • Transformers 4.26.0.dev0
  • Pytorch 1.13.0+cu117
  • Datasets 2.7.1.dev0
  • Tokenizers 0.13.2