whisper-tiny-mixed-pt
This model is a fine-tuned version of openai/whisper-tiny on an unknown dataset.
It achieves the following results on the evaluation set:
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: 5e-05
- train_batch_size: 256
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
Training results
Training Loss |
Epoch |
Step |
Validation Loss |
0.7238 |
0.3106 |
50 |
0.6113 |
0.5182 |
0.6211 |
100 |
0.5399 |
0.4443 |
0.9317 |
150 |
0.5106 |
0.3415 |
1.2422 |
200 |
0.4937 |
0.3267 |
1.5528 |
250 |
0.4779 |
0.3297 |
1.8634 |
300 |
0.4626 |
0.2069 |
2.1739 |
350 |
0.4610 |
0.2109 |
2.4845 |
400 |
0.4591 |
0.2035 |
2.7950 |
450 |
0.4559 |
0.1596 |
3.1056 |
500 |
0.4587 |
0.1377 |
3.4161 |
550 |
0.4575 |
0.1444 |
3.7267 |
600 |
0.4655 |
0.1298 |
4.0373 |
650 |
0.4626 |
0.0952 |
4.3478 |
700 |
0.4714 |
0.0986 |
4.6584 |
750 |
0.4734 |
0.103 |
4.9689 |
800 |
0.4755 |
0.0654 |
5.2795 |
850 |
0.4845 |
0.0702 |
5.5901 |
900 |
0.4876 |
0.0674 |
5.9006 |
950 |
0.4907 |
0.0442 |
6.2112 |
1000 |
0.4982 |
0.049 |
6.5217 |
1050 |
0.5013 |
0.049 |
6.8323 |
1100 |
0.5035 |
0.0353 |
7.1429 |
1150 |
0.5138 |
0.0337 |
7.4534 |
1200 |
0.5159 |
0.0347 |
7.7640 |
1250 |
0.5165 |
0.0291 |
8.0745 |
1300 |
0.5210 |
0.0259 |
8.3851 |
1350 |
0.5232 |
0.0276 |
8.6957 |
1400 |
0.5256 |
0.0254 |
9.0062 |
1450 |
0.5257 |
0.0232 |
9.3168 |
1500 |
0.5303 |
0.0227 |
9.6273 |
1550 |
0.5297 |
0.0219 |
9.9379 |
1600 |
0.5304 |
Framework versions
- Transformers 4.50.2
- Pytorch 2.5.1+cu124
- Datasets 3.6.0
- Tokenizers 0.21.2