README.md

metadata

license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - common_voice_11_0
metrics:
  - wer
model-index:
  - name: Jingmiao/whisper-small-chinese_base
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: common_voice_11_0
          type: common_voice_11_0
          config: zh-TW
          split: test
          args: zh-TW
        metrics:
          - name: Wer
            type: wer
            value: 42.64073694984647

Jingmiao/whisper-small-chinese_base

This model is a fine-tuned version of Jingmiao/whisper-small-chinese_base on the common_voice_11_0 dataset. It achieves the following results on the evaluation set:

• Loss: 0.2901
• Wer: 42.6407

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
0.0071	6.02	1000	0.2364	42.6407
0.0008	13.02	2000	0.2601	41.9038
0.0004	20.01	3000	0.2771	42.3951
0.0003	27.0	4000	0.2867	42.6407
0.0002	33.02	5000	0.2901	42.6407

Framework versions

• Transformers 4.26.0.dev0
• Pytorch 1.13.1+cu117
• Datasets 2.8.1.dev0
• Tokenizers 0.13.2