wav2vec2-base-finetuned-ic-slurp
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: 2.1101
- Accuracy: 0.7393
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: 24
- eval_batch_size: 24
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 96
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 50
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 4.0345 | 1.0 | 527 | 3.9813 | 0.0673 |
| 3.5622 | 2.0 | 1055 | 3.4634 | 0.1867 |
| 2.7737 | 3.0 | 1582 | 2.7252 | 0.3638 |
| 2.1285 | 4.0 | 2110 | 2.1754 | 0.4827 |
| 1.6216 | 5.0 | 2637 | 1.8169 | 0.5701 |
| 1.1786 | 6.0 | 3165 | 1.5773 | 0.6347 |
| 0.8747 | 7.0 | 3692 | 1.5024 | 0.6568 |
| 0.7565 | 8.0 | 4220 | 1.5020 | 0.6694 |
| 0.5236 | 9.0 | 4747 | 1.5287 | 0.6799 |
| 0.4517 | 10.0 | 5275 | 1.5165 | 0.6879 |
| 0.364 | 11.0 | 5802 | 1.5159 | 0.6949 |
| 0.3221 | 12.0 | 6330 | 1.5217 | 0.6996 |
| 0.227 | 13.0 | 6857 | 1.5718 | 0.7075 |
| 0.1828 | 14.0 | 7385 | 1.6979 | 0.6901 |
| 0.1691 | 15.0 | 7912 | 1.6162 | 0.7093 |
| 0.1642 | 16.0 | 8440 | 1.6973 | 0.7048 |
| 0.1254 | 17.0 | 8967 | 1.7060 | 0.7100 |
| 0.1578 | 18.0 | 9495 | 1.7328 | 0.7063 |
| 0.1509 | 19.0 | 10022 | 1.7658 | 0.7073 |
| 0.1409 | 20.0 | 10550 | 1.7770 | 0.7052 |
| 0.1085 | 21.0 | 11077 | 1.8033 | 0.7074 |
| 0.106 | 22.0 | 11605 | 1.7000 | 0.7149 |
| 0.0764 | 23.0 | 12132 | 1.7943 | 0.7104 |
| 0.0671 | 24.0 | 12660 | 1.8323 | 0.7155 |
| 0.0768 | 25.0 | 13187 | 1.8486 | 0.7146 |
| 0.0741 | 26.0 | 13715 | 1.8227 | 0.7187 |
| 0.0731 | 27.0 | 14242 | 1.7824 | 0.7230 |
| 0.0935 | 28.0 | 14770 | 1.8987 | 0.7164 |
| 0.0829 | 29.0 | 15297 | 1.8774 | 0.7202 |
| 0.0588 | 30.0 | 15825 | 1.8820 | 0.7211 |
| 0.059 | 31.0 | 16352 | 1.9535 | 0.7246 |
| 0.0431 | 32.0 | 16880 | 1.9621 | 0.7237 |
| 0.0324 | 33.0 | 17407 | 2.0160 | 0.7256 |
| 0.0447 | 34.0 | 17935 | 1.9392 | 0.7262 |
| 0.025 | 35.0 | 18462 | 2.0095 | 0.7284 |
| 0.0522 | 36.0 | 18990 | 1.9994 | 0.7244 |
| 0.0482 | 37.0 | 19517 | 2.0566 | 0.7262 |
| 0.0203 | 38.0 | 20045 | 2.0287 | 0.7295 |
| 0.0221 | 39.0 | 20572 | 2.0634 | 0.7300 |
| 0.0444 | 40.0 | 21100 | 2.0593 | 0.7302 |
| 0.0348 | 41.0 | 21627 | 2.0712 | 0.7298 |
| 0.0154 | 42.0 | 22155 | 2.0429 | 0.7351 |
| 0.024 | 43.0 | 22682 | 2.0708 | 0.7352 |
| 0.0157 | 44.0 | 23210 | 2.0701 | 0.7368 |
| 0.0222 | 45.0 | 23737 | 2.0963 | 0.7338 |
| 0.0126 | 46.0 | 24265 | 2.1329 | 0.7340 |
| 0.0211 | 47.0 | 24792 | 2.1230 | 0.7370 |
| 0.0288 | 48.0 | 25320 | 2.1101 | 0.7393 |
| 0.0347 | 49.0 | 25847 | 2.1201 | 0.7375 |
| 0.0162 | 49.95 | 26350 | 2.1197 | 0.7381 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.2.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2
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