metadata
language:
- zh
base_model: sit-justin/whisper-small-test
tags:
- generated_from_trainer
datasets:
- custom_datset
model-index:
- name: Whisper Small Chinese MOE Response
results: []
Whisper Small Chinese MOE Response
This model is a fine-tuned version of sit-justin/whisper-small-test on the MOE Response Chinese dataset. It achieves the following results on the evaluation set:
- Loss: 0.0158
- Cer: 2.5487
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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 250
- training_steps: 2000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Cer |
|---|---|---|---|---|
| 0.0804 | 0.5405 | 200 | 0.0771 | 5.5753 |
| 0.0695 | 1.0811 | 400 | 0.0632 | 5.4650 |
| 0.0374 | 1.6216 | 600 | 0.0467 | 4.6808 |
| 0.0228 | 2.1622 | 800 | 0.0439 | 4.9994 |
| 0.0142 | 2.7027 | 1000 | 0.0339 | 3.4310 |
| 0.0068 | 3.2432 | 1200 | 0.0257 | 5.1587 |
| 0.005 | 3.7838 | 1400 | 0.0216 | 2.7815 |
| 0.0019 | 4.3243 | 1600 | 0.0176 | 2.3772 |
| 0.0023 | 4.8649 | 1800 | 0.0158 | 2.5242 |
| 0.0012 | 5.4054 | 2000 | 0.0158 | 2.5487 |
Framework versions
- Transformers 4.42.3
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1