zh-CN-model - whucedar
This model is a fine-tuned version of openai/whisper-small on the zh-CN dataset. It achieves the following results on the evaluation set:
- Loss: 0.3881
- Wer: 134.2494
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: 50
- training_steps: 500
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.375 | 0.6897 | 100 | 0.4223 | 331.7557 |
| 0.2198 | 1.3793 | 200 | 0.3885 | 178.8295 |
| 0.0881 | 2.0690 | 300 | 0.3812 | 123.1552 |
| 0.0877 | 2.7586 | 400 | 0.3873 | 132.3155 |
| 0.0604 | 3.4483 | 500 | 0.3881 | 134.2494 |
Framework versions
- Transformers 4.42.3
- Pytorch 2.3.1+cu118
- Datasets 2.20.0
- Tokenizers 0.19.1
- Downloads last month
- 4
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.