hubert-base-ls960-finetuned-ic-slurp-wt_init-frz-v1
This model is a fine-tuned version of facebook/hubert-base-ls960 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 3.8557
- Accuracy: 0.4665
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 |
|---|---|---|---|---|
| 3.6161 | 1.0 | 527 | 3.6149 | 0.1639 |
| 3.4319 | 2.0 | 1055 | 3.4045 | 0.1837 |
| 3.2109 | 3.0 | 1582 | 3.1534 | 0.2204 |
| 3.0227 | 4.0 | 2110 | 3.0869 | 0.2425 |
| 2.7612 | 5.0 | 2637 | 2.8947 | 0.2796 |
| 2.6536 | 6.0 | 3165 | 2.7741 | 0.3162 |
| 2.2984 | 7.0 | 3692 | 2.5992 | 0.3517 |
| 2.2411 | 8.0 | 4220 | 2.5695 | 0.3678 |
| 2.0698 | 9.0 | 4747 | 2.5301 | 0.3828 |
| 1.781 | 10.0 | 5275 | 2.4942 | 0.4076 |
| 1.7756 | 11.0 | 5802 | 2.4456 | 0.4145 |
| 1.429 | 12.0 | 6330 | 2.4907 | 0.4214 |
| 1.4662 | 13.0 | 6857 | 2.5513 | 0.4287 |
| 1.2868 | 14.0 | 7385 | 2.6220 | 0.4254 |
| 1.0628 | 15.0 | 7912 | 2.6932 | 0.4294 |
| 1.0636 | 16.0 | 8440 | 2.7047 | 0.4348 |
| 0.861 | 17.0 | 8967 | 2.7132 | 0.4405 |
| 0.8748 | 18.0 | 9495 | 2.8117 | 0.4414 |
| 0.7779 | 19.0 | 10022 | 2.8338 | 0.4454 |
| 0.7247 | 20.0 | 10550 | 2.9349 | 0.4407 |
| 0.6041 | 21.0 | 11077 | 2.9980 | 0.4396 |
| 0.6234 | 22.0 | 11605 | 3.0899 | 0.4418 |
| 0.4641 | 23.0 | 12132 | 3.1206 | 0.4470 |
| 0.5321 | 24.0 | 12660 | 3.2098 | 0.4427 |
| 0.4293 | 25.0 | 13187 | 3.2953 | 0.4414 |
| 0.5322 | 26.0 | 13715 | 3.2976 | 0.4458 |
| 0.3345 | 27.0 | 14242 | 3.3888 | 0.4441 |
| 0.4868 | 28.0 | 14770 | 3.3955 | 0.4472 |
| 0.29 | 29.0 | 15297 | 3.4445 | 0.4451 |
| 0.2429 | 30.0 | 15825 | 3.4317 | 0.4537 |
| 0.3375 | 31.0 | 16352 | 3.4972 | 0.4534 |
| 0.26 | 32.0 | 16880 | 3.6675 | 0.4434 |
| 0.2337 | 33.0 | 17407 | 3.5817 | 0.4491 |
| 0.2984 | 34.0 | 17935 | 3.5766 | 0.4485 |
| 0.2249 | 35.0 | 18462 | 3.5912 | 0.4538 |
| 0.1962 | 36.0 | 18990 | 3.6414 | 0.4556 |
| 0.2243 | 37.0 | 19517 | 3.7025 | 0.4563 |
| 0.2169 | 38.0 | 20045 | 3.7524 | 0.4557 |
| 0.1509 | 39.0 | 20572 | 3.6993 | 0.4583 |
| 0.2106 | 40.0 | 21100 | 3.8040 | 0.4550 |
| 0.224 | 41.0 | 21627 | 3.7628 | 0.4628 |
| 0.1154 | 42.0 | 22155 | 3.7545 | 0.4652 |
| 0.1453 | 43.0 | 22682 | 3.7632 | 0.4651 |
| 0.1221 | 44.0 | 23210 | 3.8144 | 0.4596 |
| 0.1419 | 45.0 | 23737 | 3.8580 | 0.4627 |
| 0.1178 | 46.0 | 24265 | 3.8238 | 0.4656 |
| 0.1517 | 47.0 | 24792 | 3.8614 | 0.4635 |
| 0.1207 | 48.0 | 25320 | 3.8786 | 0.4644 |
| 0.1223 | 49.0 | 25847 | 3.8557 | 0.4665 |
| 0.067 | 49.95 | 26350 | 3.8611 | 0.4651 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.2.1+cu118
- Datasets 2.17.0
- Tokenizers 0.15.0
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