wav2vec2-large-xls-r-300m-korean_y_freq
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4522
- Cer: 13.5023
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: 0.0001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Cer |
|---|---|---|---|---|
| 35.2803 | 0.13 | 200 | 5.5453 | 100.0 |
| 4.6452 | 0.26 | 400 | 4.6065 | 100.0 |
| 4.5568 | 0.39 | 600 | 4.5732 | 97.9643 |
| 4.492 | 0.52 | 800 | 4.5091 | 97.9643 |
| 4.343 | 0.64 | 1000 | 4.2369 | 95.5012 |
| 3.3778 | 0.77 | 1200 | 2.7151 | 49.3917 |
| 2.4127 | 0.9 | 1400 | 2.2297 | 42.1509 |
| 2.0113 | 1.03 | 1600 | 1.8500 | 35.5926 |
| 1.7037 | 1.16 | 1800 | 1.5783 | 31.7942 |
| 1.502 | 1.29 | 2000 | 1.4251 | 29.2184 |
| 1.3376 | 1.42 | 2200 | 1.3812 | 30.4232 |
| 1.2586 | 1.55 | 2400 | 1.1952 | 25.6751 |
| 1.1415 | 1.68 | 2600 | 1.1614 | 25.8176 |
| 1.0858 | 1.81 | 2800 | 1.0985 | 24.9154 |
| 0.9846 | 1.93 | 3000 | 0.9985 | 21.8826 |
| 0.9443 | 2.06 | 3200 | 0.8759 | 19.9359 |
| 0.8298 | 2.19 | 3400 | 0.8549 | 19.5798 |
| 0.8111 | 2.32 | 3600 | 0.8271 | 22.2506 |
| 0.7507 | 2.45 | 3800 | 0.7808 | 20.9389 |
| 0.7202 | 2.58 | 4000 | 0.7409 | 19.5323 |
| 0.7121 | 2.71 | 4200 | 0.7139 | 18.5649 |
| 0.6639 | 2.84 | 4400 | 0.6726 | 17.4669 |
| 0.6595 | 2.97 | 4600 | 0.6830 | 16.6301 |
| 0.6161 | 3.09 | 4800 | 0.6334 | 15.5677 |
| 0.5604 | 3.22 | 5000 | 0.5943 | 14.4460 |
| 0.5387 | 3.35 | 5200 | 0.6169 | 15.4727 |
| 0.5317 | 3.48 | 5400 | 0.5831 | 15.0751 |
| 0.5171 | 3.61 | 5600 | 0.5414 | 14.3807 |
| 0.5 | 3.74 | 5800 | 0.5307 | 14.1789 |
| 0.4888 | 3.87 | 6000 | 0.5171 | 14.4875 |
| 0.4826 | 4.0 | 6200 | 0.5011 | 13.9712 |
| 0.4311 | 4.13 | 6400 | 0.5131 | 14.2679 |
| 0.4178 | 4.26 | 6600 | 0.4929 | 14.0364 |
| 0.3999 | 4.38 | 6800 | 0.4791 | 14.3451 |
| 0.4029 | 4.51 | 7000 | 0.4885 | 13.8584 |
| 0.3922 | 4.64 | 7200 | 0.4759 | 14.2323 |
| 0.3804 | 4.77 | 7400 | 0.4584 | 13.6091 |
| 0.3748 | 4.9 | 7600 | 0.4522 | 13.5023 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.0
- Tokenizers 0.15.0