whisper-small-mixed-pt
This model is a fine-tuned version of openai/whisper-small 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: 1e-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 |
0.6023 |
0.3106 |
50 |
0.3002 |
0.3097 |
0.6211 |
100 |
0.2405 |
0.2589 |
0.9317 |
150 |
0.2234 |
0.2016 |
1.2422 |
200 |
0.2189 |
0.1889 |
1.5528 |
250 |
0.2138 |
0.1971 |
1.8634 |
300 |
0.2099 |
0.1277 |
2.1739 |
350 |
0.2135 |
0.128 |
2.4845 |
400 |
0.2126 |
0.121 |
2.7950 |
450 |
0.2132 |
0.1029 |
3.1056 |
500 |
0.2169 |
0.0854 |
3.4161 |
550 |
0.2200 |
0.0926 |
3.7267 |
600 |
0.2206 |
0.0814 |
4.0373 |
650 |
0.2234 |
0.0654 |
4.3478 |
700 |
0.2297 |
0.064 |
4.6584 |
750 |
0.2330 |
0.0686 |
4.9689 |
800 |
0.2305 |
0.0464 |
5.2795 |
850 |
0.2413 |
0.0491 |
5.5901 |
900 |
0.2444 |
0.0458 |
5.9006 |
950 |
0.2431 |
0.0339 |
6.2112 |
1000 |
0.2545 |
0.0354 |
6.5217 |
1050 |
0.2567 |
0.0361 |
6.8323 |
1100 |
0.2549 |
0.0274 |
7.1429 |
1150 |
0.2630 |
0.0266 |
7.4534 |
1200 |
0.2621 |
0.0273 |
7.7640 |
1250 |
0.2646 |
0.0237 |
8.0745 |
1300 |
0.2671 |
0.0223 |
8.3851 |
1350 |
0.2701 |
0.0236 |
8.6957 |
1400 |
0.2723 |
0.0212 |
9.0062 |
1450 |
0.2720 |
0.0203 |
9.3168 |
1500 |
0.2745 |
0.0191 |
9.6273 |
1550 |
0.2747 |
0.0191 |
9.9379 |
1600 |
0.2749 |
Framework versions
- Transformers 4.50.2
- Pytorch 2.5.1+cu124
- Datasets 3.6.0
- Tokenizers 0.21.2