k2e-20s_asr-scr_w2v2-base_001
This model is a fine-tuned version of facebook/wav2vec2-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.5230
- Per: 0.1454
- Pcc: 0.5490
- Ctc Loss: 0.5155
- Mse Loss: 0.9906
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: 1
- seed: 1111
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2235
- training_steps: 22350
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Per | Pcc | Ctc Loss | Mse Loss |
---|---|---|---|---|---|---|---|
42.4921 | 1.0 | 745 | 19.1354 | 0.9890 | 0.1755 | 6.0201 | 13.1446 |
9.6761 | 2.0 | 1490 | 4.8873 | 0.9890 | 0.3766 | 3.8628 | 1.0511 |
4.7811 | 3.0 | 2235 | 4.6462 | 0.9890 | 0.5747 | 3.8063 | 0.9061 |
4.5636 | 4.01 | 2980 | 4.4298 | 0.9890 | 0.5829 | 3.7773 | 0.7581 |
4.3976 | 5.01 | 3725 | 4.3800 | 0.9890 | 0.6088 | 3.7597 | 0.7604 |
4.2244 | 6.01 | 4470 | 4.4381 | 0.9890 | 0.5888 | 3.6791 | 0.9234 |
4.0281 | 7.01 | 5215 | 4.4452 | 0.9890 | 0.5979 | 3.6172 | 1.0127 |
3.8406 | 8.01 | 5960 | 4.3227 | 0.9884 | 0.5790 | 3.5061 | 1.0160 |
3.4504 | 9.01 | 6705 | 3.7651 | 0.9557 | 0.5562 | 2.8520 | 1.0726 |
2.6451 | 10.01 | 7450 | 3.2489 | 0.6173 | 0.5703 | 1.9227 | 1.3898 |
1.89 | 11.01 | 8195 | 2.1831 | 0.3574 | 0.5481 | 1.2651 | 0.9472 |
1.4355 | 12.02 | 8940 | 2.1442 | 0.2583 | 0.5619 | 0.9769 | 1.1527 |
1.2033 | 13.02 | 9685 | 1.8016 | 0.2317 | 0.5534 | 0.8432 | 0.9477 |
1.0366 | 14.02 | 10430 | 1.9141 | 0.2145 | 0.5525 | 0.7478 | 1.1287 |
0.9253 | 15.02 | 11175 | 1.9080 | 0.2019 | 0.5479 | 0.6880 | 1.1717 |
0.8488 | 16.02 | 11920 | 1.6636 | 0.1923 | 0.5558 | 0.6417 | 0.9913 |
0.7648 | 17.02 | 12665 | 1.5709 | 0.1837 | 0.5517 | 0.6131 | 0.9345 |
0.7179 | 18.02 | 13410 | 1.6913 | 0.1798 | 0.5501 | 0.5893 | 1.0623 |
0.6645 | 19.03 | 14155 | 1.6498 | 0.1760 | 0.5565 | 0.5766 | 1.0380 |
0.6345 | 20.03 | 14900 | 1.7144 | 0.1741 | 0.5650 | 0.5604 | 1.1090 |
0.5919 | 21.03 | 15645 | 1.6624 | 0.1719 | 0.5581 | 0.5480 | 1.0756 |
0.5616 | 22.03 | 16390 | 1.5461 | 0.1695 | 0.5629 | 0.5467 | 0.9780 |
0.5371 | 23.03 | 17135 | 1.5791 | 0.1674 | 0.5533 | 0.5360 | 1.0165 |
0.5074 | 24.03 | 17880 | 1.5947 | 0.1662 | 0.5474 | 0.5267 | 1.0386 |
0.4922 | 25.03 | 18625 | 1.4868 | 0.1652 | 0.5489 | 0.5250 | 0.9494 |
0.473 | 26.03 | 19370 | 1.5373 | 0.1646 | 0.5576 | 0.5226 | 0.9952 |
0.4671 | 27.04 | 20115 | 1.5479 | 0.1638 | 0.5540 | 0.5201 | 1.0069 |
0.452 | 28.04 | 20860 | 1.5199 | 0.1635 | 0.5555 | 0.5163 | 0.9869 |
0.4435 | 29.04 | 21605 | 1.5116 | 0.1634 | 0.5544 | 0.5154 | 0.9810 |
0.439 | 30.04 | 22350 | 1.5230 | 0.1633 | 0.5567 | 0.5155 | 0.9906 |
Framework versions
- Transformers 4.38.1
- Pytorch 2.0.1
- Datasets 2.16.1
- Tokenizers 0.15.2
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Model tree for excalibur12/k2e-20s_asr-scr_w2v2-base_001
Base model
facebook/wav2vec2-base