metadata
library_name: transformers
language:
- zh
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: Whisper_largev3_motor_zh
results: []
Whisper_largev3_motor_zh
This model is a fine-tuned version of openai/whisper-large-v3 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1577
- Wer: 675.0
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: 4
- 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: 25
- training_steps: 500
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.2805 | 0.0302 | 100 | 0.2447 | 47.4359 |
| 0.2094 | 0.0603 | 200 | 0.1964 | 472.3157 |
| 0.1738 | 0.0905 | 300 | 0.1827 | 424.5192 |
| 0.2119 | 0.1206 | 400 | 0.1679 | 489.3630 |
| 0.1629 | 0.1508 | 500 | 0.1577 | 675.0 |
Framework versions
- Transformers 4.45.2
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.20.3