lg-digits-classification
This model is a fine-tuned version of facebook/wav2vec2-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.5405
- Accuracy: 0.6087
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: 4
- eval_batch_size: 1
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 50
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.9211 | 1.0 | 47 | 2.0718 | 0.2174 |
| 1.9034 | 2.0 | 94 | 2.0263 | 0.2174 |
| 1.8375 | 3.0 | 141 | 2.1374 | 0.2609 |
| 1.7839 | 4.0 | 188 | 2.0091 | 0.3043 |
| 1.6964 | 5.0 | 235 | 2.0135 | 0.2609 |
| 1.6485 | 6.0 | 282 | 1.9707 | 0.4348 |
| 1.5452 | 7.0 | 329 | 1.8629 | 0.3043 |
| 1.4662 | 8.0 | 376 | 1.8037 | 0.4348 |
| 1.3512 | 9.0 | 423 | 1.6884 | 0.5217 |
| 1.2567 | 10.0 | 470 | 1.7180 | 0.5652 |
| 1.1825 | 11.0 | 517 | 1.5855 | 0.5652 |
| 1.0535 | 12.0 | 564 | 1.6781 | 0.4783 |
| 0.9519 | 13.0 | 611 | 1.5681 | 0.5652 |
| 0.9136 | 14.0 | 658 | 1.4914 | 0.6087 |
| 0.7924 | 15.0 | 705 | 1.7370 | 0.5652 |
| 0.6775 | 16.0 | 752 | 1.6007 | 0.5652 |
| 0.7597 | 17.0 | 799 | 1.5242 | 0.6087 |
| 0.5731 | 18.0 | 846 | 1.7712 | 0.6087 |
| 0.5235 | 19.0 | 893 | 1.5915 | 0.5652 |
| 0.5463 | 20.0 | 940 | 1.7188 | 0.5652 |
| 0.4434 | 21.0 | 987 | 1.8435 | 0.5652 |
| 0.3921 | 22.0 | 1034 | 1.8180 | 0.6522 |
| 0.4408 | 23.0 | 1081 | 1.9594 | 0.5652 |
| 0.3323 | 24.0 | 1128 | 1.9446 | 0.5652 |
| 0.2806 | 25.0 | 1175 | 1.9466 | 0.5652 |
| 0.2228 | 26.0 | 1222 | 2.1430 | 0.5652 |
| 0.3144 | 27.0 | 1269 | 2.2630 | 0.5652 |
| 0.2841 | 28.0 | 1316 | 2.1039 | 0.5652 |
| 0.2392 | 29.0 | 1363 | 2.1887 | 0.6087 |
| 0.1964 | 30.0 | 1410 | 2.1597 | 0.6522 |
| 0.2014 | 31.0 | 1457 | 2.2470 | 0.6087 |
| 0.194 | 32.0 | 1504 | 2.3058 | 0.5652 |
| 0.202 | 33.0 | 1551 | 2.4327 | 0.5652 |
| 0.1968 | 34.0 | 1598 | 2.4571 | 0.5652 |
| 0.1675 | 35.0 | 1645 | 2.4031 | 0.6087 |
| 0.2261 | 36.0 | 1692 | 2.4036 | 0.6087 |
| 0.279 | 37.0 | 1739 | 2.4073 | 0.6087 |
| 0.2378 | 38.0 | 1786 | 2.4481 | 0.6087 |
| 0.2414 | 39.0 | 1833 | 2.4839 | 0.6087 |
| 0.189 | 40.0 | 1880 | 2.5730 | 0.5652 |
| 0.2018 | 41.0 | 1927 | 2.6159 | 0.5652 |
| 0.2418 | 42.0 | 1974 | 2.4725 | 0.5652 |
| 0.1489 | 43.0 | 2021 | 2.4596 | 0.5652 |
| 0.2277 | 44.0 | 2068 | 2.4913 | 0.6087 |
| 0.2313 | 45.0 | 2115 | 2.4922 | 0.6087 |
| 0.2333 | 46.0 | 2162 | 2.4951 | 0.6087 |
| 0.2201 | 47.0 | 2209 | 2.5213 | 0.6087 |
| 0.2116 | 48.0 | 2256 | 2.5164 | 0.6087 |
| 0.2122 | 49.0 | 2303 | 2.5424 | 0.6087 |
| 0.1965 | 50.0 | 2350 | 2.5405 | 0.6087 |
Framework versions
- Transformers 4.56.2
- Pytorch 2.8.0+cu128
- Datasets 3.6.0
- Tokenizers 0.22.1