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korean-aihub-learning-math-1-test
This model is a fine-tuned version of kresnik/wav2vec2-large-xlsr-korean on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.2537
- Wer: 0.4765
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: 0.0003
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 30
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| No log | 1.0 | 35 | 29.8031 | 1.0 |
| No log | 2.0 | 70 | 5.7158 | 1.0 |
| 19.8789 | 3.0 | 105 | 4.5005 | 1.0 |
| 19.8789 | 4.0 | 140 | 4.3677 | 0.9984 |
| 19.8789 | 5.0 | 175 | 3.8013 | 0.9882 |
| 3.9785 | 6.0 | 210 | 2.4132 | 0.8730 |
| 3.9785 | 7.0 | 245 | 1.5867 | 0.7045 |
| 3.9785 | 8.0 | 280 | 1.3179 | 0.6082 |
| 1.2266 | 9.0 | 315 | 1.2431 | 0.6066 |
| 1.2266 | 10.0 | 350 | 1.1791 | 0.5384 |
| 1.2266 | 11.0 | 385 | 1.0994 | 0.5298 |
| 0.3916 | 12.0 | 420 | 1.1552 | 0.5196 |
| 0.3916 | 13.0 | 455 | 1.1495 | 0.5486 |
| 0.3916 | 14.0 | 490 | 1.1340 | 0.5290 |
| 0.2488 | 15.0 | 525 | 1.2208 | 0.5525 |
| 0.2488 | 16.0 | 560 | 1.1682 | 0.5024 |
| 0.2488 | 17.0 | 595 | 1.1479 | 0.5008 |
| 0.1907 | 18.0 | 630 | 1.1735 | 0.4882 |
| 0.1907 | 19.0 | 665 | 1.2302 | 0.4914 |
| 0.1461 | 20.0 | 700 | 1.2497 | 0.4890 |
| 0.1461 | 21.0 | 735 | 1.2434 | 0.4914 |
| 0.1461 | 22.0 | 770 | 1.2031 | 0.5031 |
| 0.1147 | 23.0 | 805 | 1.2451 | 0.4976 |
| 0.1147 | 24.0 | 840 | 1.2746 | 0.4937 |
| 0.1147 | 25.0 | 875 | 1.2405 | 0.4828 |
| 0.0892 | 26.0 | 910 | 1.2228 | 0.4929 |
| 0.0892 | 27.0 | 945 | 1.2642 | 0.4898 |
| 0.0892 | 28.0 | 980 | 1.2586 | 0.4843 |
| 0.0709 | 29.0 | 1015 | 1.2518 | 0.4788 |
| 0.0709 | 30.0 | 1050 | 1.2537 | 0.4765 |
Framework versions
- Transformers 4.20.1
- Pytorch 1.12.0+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1
