whisper-tiny-cn-1 / README.md
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metadata
language:
  - zh
license: apache-2.0
base_model: xmzhu/whisper-tiny-zh
tags:
  - whisper-event
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_16_0
metrics:
  - wer
model-index:
  - name: Whisper Base Chinese-Mandarin
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: mozilla-foundation/common_voice_16_0 zh-CN
          type: mozilla-foundation/common_voice_16_0
          config: zh-CN
          split: test
          args: zh-CN
        metrics:
          - name: Wer
            type: wer
            value: 91.12657677250978

Whisper Base Chinese-Mandarin

This model is a fine-tuned version of xmzhu/whisper-tiny-zh on the mozilla-foundation/common_voice_16_0 zh-CN dataset. It achieves the following results on the evaluation set:

  • Loss: 0.5759
  • Wer: 91.1266

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: 5e-07
  • train_batch_size: 32
  • eval_batch_size: 32
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 64
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 200
  • training_steps: 1000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.6689 0.2 200 0.5854 91.6311
0.6314 1.07 400 0.5791 91.1788
0.653 1.27 600 0.5759 91.1266
0.699 2.13 800 0.5749 91.2049
0.5613 3.0 1000 0.5744 91.1527

Framework versions

  • Transformers 4.37.0.dev0
  • Pytorch 2.1.2+cu121
  • Datasets 2.16.2.dev0
  • Tokenizers 0.15.0