README.md

metadata

license: apache-2.0
tags:
  - whisper-event
  - generated_from_trainer
datasets:
  - google/fleurs
metrics:
  - wer
model-index:
  - name: Whisper Small Chinese Base
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: google/fleurs cmn_hans_cn
          type: google/fleurs
          config: cmn_hans_cn
          split: test
          args: cmn_hans_cn
        metrics:
          - name: Wer
            type: wer
            value: 14.92818317087243

Whisper Small Chinese Base

This model is a fine-tuned version of openai/whisper-small on the google/fleurs cmn_hans_cn dataset. It achieves the following results on the evaluation set:

• Loss: 0.2910
• Wer: 14.9282

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
0.0013	19.01	1000	0.2910	14.9282
0.0005	39.0	2000	0.3185	15.6327
0.0002	58.01	3000	0.3369	15.6965
0.0002	78.0	4000	0.3480	16.0669
0.0001	98.0	5000	0.3537	16.0548

Framework versions

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