metadata
library_name: transformers
license: apache-2.0
base_model: openai/whisper-base
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-base-zh
results: []
whisper-base-zh
This model is a fine-tuned version of openai/whisper-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3426
- Wer: 78.6221
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: 5e-06
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- training_steps: 4000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.4992 | 0.2075 | 100 | 0.4841 | 93.0091 |
| 0.4325 | 0.4149 | 200 | 0.4223 | 82.7761 |
| 0.4028 | 0.6224 | 300 | 0.3979 | 81.6616 |
| 0.3866 | 0.8299 | 400 | 0.3846 | 79.8886 |
| 0.3322 | 1.0373 | 500 | 0.3731 | 80.3951 |
| 0.3108 | 1.2448 | 600 | 0.3672 | 79.2300 |
| 0.3139 | 1.4523 | 700 | 0.3601 | 79.1287 |
| 0.324 | 1.6598 | 800 | 0.3558 | 78.7741 |
| 0.2629 | 1.8672 | 900 | 0.3525 | 78.1155 |
| 0.2421 | 2.0747 | 1000 | 0.3521 | 78.5208 |
| 0.217 | 2.2822 | 1100 | 0.3495 | 78.3688 |
| 0.2071 | 2.4896 | 1200 | 0.3490 | 78.5714 |
| 0.2183 | 2.6971 | 1300 | 0.3452 | 78.6727 |
| 0.2158 | 2.9046 | 1400 | 0.3426 | 78.6221 |
Framework versions
- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3