whisper-small-sagale_dataset-ormo-10hrs-v5
This model is a fine-tuned version of openai/whisper-small on an unknown dataset. It achieves the following results on the evaluation set:
- Wer: 0.3355
- Cer: 0.1622
- Loss: 0.1740
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: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Use adamw_bnb_8bit 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: 0.05
- num_epochs: 100
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Wer | Cer | Validation Loss |
---|---|---|---|---|---|
1.6671 | 1.0 | 196 | 0.9903 | 0.6375 | 0.8798 |
0.2728 | 2.0 | 392 | 0.4929 | 0.2124 | 0.1525 |
0.1106 | 3.0 | 588 | 0.4350 | 0.1909 | 0.1279 |
0.076 | 4.0 | 784 | 0.4198 | 0.1929 | 0.1284 |
0.062 | 5.0 | 980 | 0.4264 | 0.1937 | 0.1381 |
0.0525 | 6.0 | 1176 | 0.3942 | 0.1791 | 0.1289 |
0.0399 | 7.0 | 1372 | 0.4073 | 0.1897 | 0.1321 |
0.032 | 8.0 | 1568 | 0.3698 | 0.1702 | 0.1303 |
0.0246 | 9.0 | 1764 | 0.3831 | 0.1746 | 0.1446 |
0.0214 | 10.0 | 1960 | 0.3674 | 0.1705 | 0.1477 |
0.0164 | 11.0 | 2156 | 0.3711 | 0.1713 | 0.1485 |
0.0133 | 12.0 | 2352 | 0.3617 | 0.1707 | 0.1479 |
0.0128 | 13.0 | 2548 | 0.3609 | 0.1722 | 0.1496 |
0.0117 | 14.0 | 2744 | 0.3628 | 0.1739 | 0.1486 |
0.0089 | 15.0 | 2940 | 0.3526 | 0.1674 | 0.1521 |
0.0088 | 16.0 | 3136 | 0.3543 | 0.1687 | 0.1598 |
0.007 | 17.0 | 3332 | 0.3588 | 0.1684 | 0.1673 |
0.0069 | 18.0 | 3528 | 0.3556 | 0.1671 | 0.1722 |
0.0065 | 19.0 | 3724 | 0.3583 | 0.1672 | 0.1751 |
0.0062 | 20.0 | 3920 | 0.3564 | 0.1660 | 0.1612 |
0.0056 | 21.0 | 4116 | 0.3473 | 0.1649 | 0.1659 |
0.0043 | 22.0 | 4312 | 0.3545 | 0.1659 | 0.1755 |
0.0049 | 23.0 | 4508 | 0.3499 | 0.1664 | 0.1664 |
0.0049 | 24.0 | 4704 | 0.3615 | 0.1686 | 0.1666 |
0.0043 | 25.0 | 4900 | 0.3528 | 0.1656 | 0.1720 |
0.0036 | 26.0 | 5096 | 0.3418 | 0.1638 | 0.1650 |
0.0035 | 27.0 | 5292 | 0.3490 | 0.1634 | 0.1826 |
0.0037 | 28.0 | 5488 | 0.3509 | 0.1679 | 0.1696 |
0.0027 | 29.0 | 5684 | 0.3439 | 0.1633 | 0.1814 |
0.0028 | 30.0 | 5880 | 0.3416 | 0.1651 | 0.1776 |
0.0032 | 31.0 | 6076 | 0.3473 | 0.1650 | 0.1674 |
0.0028 | 32.0 | 6272 | 0.3414 | 0.1632 | 0.1771 |
0.0028 | 33.0 | 6468 | 0.3357 | 0.1624 | 0.1840 |
0.0026 | 34.0 | 6664 | 0.3416 | 0.1647 | 0.1787 |
0.0031 | 35.0 | 6860 | 0.3482 | 0.1650 | 0.1855 |
0.0025 | 36.0 | 7056 | 0.3454 | 0.1631 | 0.1821 |
0.0025 | 37.0 | 7252 | 0.3475 | 0.1653 | 0.1707 |
0.0022 | 38.0 | 7448 | 0.3374 | 0.1617 | 0.1713 |
0.0016 | 39.0 | 7644 | 0.3414 | 0.1627 | 0.1781 |
0.0023 | 40.0 | 7840 | 0.3444 | 0.1630 | 0.1767 |
0.0022 | 41.0 | 8036 | 0.3374 | 0.1638 | 0.1697 |
0.0014 | 42.0 | 8232 | 0.3397 | 0.1632 | 0.1907 |
0.0018 | 43.0 | 8428 | 0.3355 | 0.1622 | 0.1740 |
Framework versions
- Transformers 4.49.0
- Pytorch 2.5.1+cu121
- Datasets 2.20.0
- Tokenizers 0.21.0
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Base model
openai/whisper-small