README.md

metadata

language:
  - zh
license: apache-2.0
tags:
  - whisper-event
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_11_0
metrics:
  - wer
model-index:
  - name: Whisper Small Chinese
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: mozilla-foundation/common_voice_11_0 zh-CN
          type: mozilla-foundation/common_voice_11_0
          config: zh-CN
          split: test
          args: zh-CN
        metrics:
          - name: Wer
            type: wer
            value: 72.36255572065379

Whisper Small Chinese

This model is a fine-tuned version of openai/whisper-small on the mozilla-foundation/common_voice_11_0 zh-CN dataset. It achieves the following results on the evaluation set:

• Loss: 0.3946
• Wer: 72.3626

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: 64
• eval_batch_size: 32
• 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: 5000
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.5179	2.02	1000	0.3333	72.9831
0.1273	4.04	2000	0.3562	73.9621
0.0163	6.06	3000	0.3790	73.9708
0.004	8.07	4000	0.3946	72.3626
0.025	11.0	5000	0.4019	72.6772

Framework versions

• Transformers 4.26.0.dev0
• Pytorch 1.13.1+cu117
• Datasets 2.7.1.dev0
• Tokenizers 0.13.2