wav2vec2-xls-r-300m-intent-classification-ori
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.3107
- Accuracy: 0.625
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: 3e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 45
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 2.1982 | 1.0 | 14 | 2.1951 | 0.0625 |
| 2.2021 | 2.0 | 28 | 2.1847 | 0.1458 |
| 2.1819 | 3.0 | 42 | 2.1661 | 0.3333 |
| 2.1789 | 4.0 | 56 | 2.1413 | 0.3333 |
| 2.164 | 5.0 | 70 | 2.1183 | 0.3333 |
| 2.1484 | 6.0 | 84 | 2.0974 | 0.3333 |
| 2.1199 | 7.0 | 98 | 2.0939 | 0.3333 |
| 2.1343 | 8.0 | 112 | 2.0829 | 0.3333 |
| 2.1397 | 9.0 | 126 | 2.0654 | 0.3333 |
| 2.1045 | 10.0 | 140 | 2.0553 | 0.3333 |
| 2.1083 | 11.0 | 154 | 2.0255 | 0.3333 |
| 2.0914 | 12.0 | 168 | 2.0065 | 0.3333 |
| 2.0434 | 13.0 | 182 | 1.9696 | 0.3333 |
| 2.0687 | 14.0 | 196 | 1.9231 | 0.4167 |
| 2.0237 | 15.0 | 210 | 1.8679 | 0.4167 |
| 1.9562 | 16.0 | 224 | 1.8184 | 0.4167 |
| 2.0361 | 17.0 | 238 | 1.8803 | 0.3958 |
| 1.888 | 18.0 | 252 | 1.7802 | 0.4167 |
| 1.899 | 19.0 | 266 | 1.7662 | 0.4167 |
| 1.8959 | 20.0 | 280 | 1.7076 | 0.4167 |
| 1.8368 | 21.0 | 294 | 1.6566 | 0.4375 |
| 1.7358 | 22.0 | 308 | 1.6283 | 0.5 |
| 1.7877 | 23.0 | 322 | 1.6411 | 0.4583 |
| 1.7311 | 24.0 | 336 | 1.5525 | 0.5208 |
| 1.7079 | 25.0 | 350 | 1.5163 | 0.5 |
| 1.6496 | 26.0 | 364 | 1.5458 | 0.5 |
| 1.6374 | 27.0 | 378 | 1.5211 | 0.5 |
| 1.6048 | 28.0 | 392 | 1.4533 | 0.5417 |
| 1.5927 | 29.0 | 406 | 1.4319 | 0.5 |
| 1.4987 | 30.0 | 420 | 1.4579 | 0.5208 |
| 1.5745 | 31.0 | 434 | 1.4167 | 0.6042 |
| 1.4632 | 32.0 | 448 | 1.4471 | 0.5417 |
| 1.4686 | 33.0 | 462 | 1.4116 | 0.5625 |
| 1.5368 | 34.0 | 476 | 1.3872 | 0.6042 |
| 1.4327 | 35.0 | 490 | 1.3491 | 0.5833 |
| 1.3978 | 36.0 | 504 | 1.3325 | 0.5833 |
| 1.4509 | 37.0 | 518 | 1.3236 | 0.6042 |
| 1.3881 | 38.0 | 532 | 1.3426 | 0.5833 |
| 1.39 | 39.0 | 546 | 1.3137 | 0.6042 |
| 1.4153 | 40.0 | 560 | 1.3123 | 0.625 |
| 1.3635 | 41.0 | 574 | 1.3224 | 0.6042 |
| 1.403 | 42.0 | 588 | 1.3111 | 0.6042 |
| 1.3763 | 43.0 | 602 | 1.3197 | 0.5833 |
| 1.3539 | 44.0 | 616 | 1.3077 | 0.6042 |
| 1.306 | 45.0 | 630 | 1.3107 | 0.625 |
Framework versions
- Transformers 4.20.1
- Pytorch 1.11.0
- Datasets 2.1.0
- Tokenizers 0.12.1