whisper-medium-fa
This model is a fine-tuned version of openai/whisper-medium on the common_voice_17_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4233
- Wer: 40.8723
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: 1000
- training_steps: 1000
Training results
| Training Loss |
Epoch |
Step |
Validation Loss |
Wer |
| 0.3796 |
0.0811 |
200 |
0.5452 |
47.2661 |
| 0.3085 |
0.1622 |
400 |
0.4883 |
44.2043 |
| 0.2575 |
0.2433 |
600 |
0.4480 |
43.2045 |
| 0.2283 |
0.3244 |
800 |
0.4262 |
40.0376 |
| 0.246 |
0.4055 |
1000 |
0.4233 |
40.8723 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.3.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
