metadata
library_name: transformers
license: apache-2.0
base_model: openai/whisper-medium
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: Fine-tuned Whisper model for Legislative Yuan of Taiwan
results: []
Fine-tuned Whisper model for Legislative Yuan of Taiwan
This model is a fine-tuned version of openai/whisper-medium on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0167
- Wer: 62.0249
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: 500
- training_steps: 5000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0161 | 0.2034 | 1000 | 0.0196 | 67.4840 |
| 0.0191 | 0.4068 | 2000 | 0.0185 | 65.3481 |
| 0.0152 | 0.6103 | 3000 | 0.0176 | 64.0898 |
| 0.0157 | 0.8137 | 4000 | 0.0171 | 62.9154 |
| 0.011 | 1.0171 | 5000 | 0.0167 | 62.0249 |
Framework versions
- Transformers 4.45.2
- Pytorch 2.5.1
- Datasets 2.19.1
- Tokenizers 0.20.1