<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. -->
korean-aihub-learning-math-16batch
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: 1.1497
- Wer: 0.5260
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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- 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 | 20 | 32.0718 | 1.0 |
No log | 2.0 | 40 | 24.7403 | 1.0808 |
No log | 3.0 | 60 | 5.8389 | 1.0 |
No log | 4.0 | 80 | 4.8543 | 1.0 |
19.6583 | 5.0 | 100 | 4.4453 | 1.0 |
19.6583 | 6.0 | 120 | 4.3923 | 1.0 |
19.6583 | 7.0 | 140 | 4.2902 | 1.0 |
19.6583 | 8.0 | 160 | 3.9026 | 0.9959 |
19.6583 | 9.0 | 180 | 3.0616 | 0.9740 |
3.7358 | 10.0 | 200 | 2.2049 | 0.8534 |
3.7358 | 11.0 | 220 | 1.6666 | 0.7288 |
3.7358 | 12.0 | 240 | 1.4123 | 0.6603 |
3.7358 | 13.0 | 260 | 1.3113 | 0.6164 |
3.7358 | 14.0 | 280 | 1.2269 | 0.6356 |
0.8398 | 15.0 | 300 | 1.2349 | 0.5945 |
0.8398 | 16.0 | 320 | 1.1970 | 0.5658 |
0.8398 | 17.0 | 340 | 1.2144 | 0.5562 |
0.8398 | 18.0 | 360 | 1.2551 | 0.5658 |
0.8398 | 19.0 | 380 | 1.1971 | 0.5493 |
0.2649 | 20.0 | 400 | 1.1967 | 0.5247 |
0.2649 | 21.0 | 420 | 1.2796 | 0.5849 |
0.2649 | 22.0 | 440 | 1.2156 | 0.5521 |
0.2649 | 23.0 | 460 | 1.2118 | 0.5425 |
0.2649 | 24.0 | 480 | 1.1637 | 0.5384 |
0.1801 | 25.0 | 500 | 1.1846 | 0.5562 |
0.1801 | 26.0 | 520 | 1.1927 | 0.5534 |
0.1801 | 27.0 | 540 | 1.2015 | 0.5384 |
0.1801 | 28.0 | 560 | 1.2077 | 0.5397 |
0.1801 | 29.0 | 580 | 1.1554 | 0.5260 |
0.1364 | 30.0 | 600 | 1.1497 | 0.5260 |
Framework versions
- Transformers 4.22.0.dev0
- Pytorch 1.12.0+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1