wav2vec2-base-mn-pretrain-42h-finetuned-speech-commands
This model is a fine-tuned version of bayartsogt/wav2vec2-base-mn-pretrain-42h on the Mongolian Speech Commands dataset. It achieves the following results on the evaluation set:
- Loss: 0.1007
- Accuracy: 0.9762
- F1: 0.9758
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: 5e-05
- train_batch_size: 128
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 2.2273 | 1.0 | 17 | 2.2714 | 0.1190 | 0.0253 |
| 1.7478 | 2.0 | 34 | 1.2036 | 0.8452 | 0.8242 |
| 0.775 | 3.0 | 51 | 0.4755 | 0.9524 | 0.9526 |
| 0.4738 | 4.0 | 68 | 0.2056 | 0.9881 | 0.9878 |
| 0.3146 | 5.0 | 85 | 0.1485 | 0.9762 | 0.9765 |
| 0.2677 | 6.0 | 102 | 0.1277 | 0.9762 | 0.9758 |
| 0.2636 | 7.0 | 119 | 0.0919 | 0.9881 | 0.9880 |
| 0.2122 | 8.0 | 136 | 0.0903 | 0.9762 | 0.9758 |
| 0.1817 | 9.0 | 153 | 0.0782 | 0.9881 | 0.9880 |
| 0.198 | 10.0 | 170 | 0.0982 | 0.9762 | 0.9758 |
| 0.1436 | 11.0 | 187 | 0.1053 | 0.9762 | 0.9758 |
| 0.1111 | 12.0 | 204 | 0.1004 | 0.9762 | 0.9758 |
| 0.1607 | 13.0 | 221 | 0.1176 | 0.9762 | 0.9758 |
| 0.1209 | 14.0 | 238 | 0.1097 | 0.9762 | 0.9758 |
| 0.0974 | 15.0 | 255 | 0.1136 | 0.9762 | 0.9758 |
| 0.1351 | 16.0 | 272 | 0.0986 | 0.9762 | 0.9758 |
| 0.1008 | 17.0 | 289 | 0.1010 | 0.9762 | 0.9758 |
| 0.097 | 18.0 | 306 | 0.0781 | 0.9762 | 0.9758 |
| 0.0806 | 19.0 | 323 | 0.1106 | 0.9762 | 0.9758 |
| 0.0744 | 20.0 | 340 | 0.1007 | 0.9762 | 0.9758 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.0
- Datasets 2.14.4
- Tokenizers 0.13.3