README.md

metadata

license: apache-2.0
tags:
  - generated_from_trainer
base_model: openai/whisper-small
datasets:
  - verba_lex_voice
metrics:
  - wer
model-index:
  - name: verbalex-zh
    results:
      - task:
          type: automatic-speech-recognition
          name: Automatic Speech Recognition
        dataset:
          name: verba_lex_voice
          type: verba_lex_voice
          config: zh
          split: test
          args: zh
        metrics:
          - type: wer
            value: 4.670558798999166
            name: Wer

verbalex-zh

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

• Loss: 0.1147
• Wer: 4.6706

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: 16
• eval_batch_size: 8
• 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: 3000
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.0025	5.0505	1000	0.1035	8.5071
0.0002	10.1010	2000	0.1130	4.7540
0.0002	15.1515	3000	0.1147	4.6706

Framework versions

• Transformers 4.40.2
• Pytorch 2.1.2
• Datasets 2.16.0
• Tokenizers 0.19.1