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: 0.0384
- Wer: 84.0803
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 |
|---|---|---|---|---|
| 0.0065 | 3.1646 | 1000 | 0.0302 | 84.9498 |
| 0.0004 | 6.3291 | 2000 | 0.0336 | 84.8161 |
| 0.0001 | 9.4937 | 3000 | 0.0363 | 84.1472 |
| 0.0 | 12.6582 | 4000 | 0.0377 | 83.8796 |
| 0.0 | 15.8228 | 5000 | 0.0384 | 84.0803 |
Framework versions
- Transformers 4.45.2
- Pytorch 2.5.1
- Datasets 2.19.1
- Tokenizers 0.20.1