metadata
language:
- zh
license: apache-2.0
base_model: sit-justin/whisper-medium-p2-moe
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-medium-p2-moe on the MOE Response Chinese dataset. It achieves the following results on the evaluation set:
- Loss: 0.0360
- Cer: 2.4470
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 |
|---|---|---|---|---|
| 0.1079 | 0.0852 | 200 | 0.1211 | 10.1923 |
| 0.1371 | 0.1704 | 400 | 0.1223 | 8.1479 |
| 0.1069 | 0.2556 | 600 | 0.1130 | 9.1791 |
| 0.1131 | 0.3409 | 800 | 0.1012 | 8.6100 |
| 0.0918 | 0.4261 | 1000 | 0.0844 | 6.0797 |
| 0.0846 | 0.5113 | 1200 | 0.0708 | 4.6004 |
| 0.0606 | 0.5965 | 1400 | 0.0594 | 4.1761 |
| 0.0545 | 0.6817 | 1600 | 0.0488 | 5.9528 |
| 0.044 | 0.7669 | 1800 | 0.0398 | 2.6056 |
| 0.0376 | 0.8522 | 2000 | 0.0360 | 2.4470 |
Framework versions
- Transformers 4.42.3
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1