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
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Model tree for RitchieP/verbalex-zh
Base model
openai/whisper-small