<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. -->
Regression_albert_9_with_translation
This model is a fine-tuned version of albert-base-v2 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3629
- Mse: 0.3629
- Mae: 0.4551
- R2: 0.1650
- Accuracy: 0.6333
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: 2e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Mse | Mae | R2 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 53 | 0.3421 | 0.3421 | 0.4573 | 0.2292 | 0.6167 |
| No log | 2.0 | 106 | 0.2617 | 0.2617 | 0.3888 | 0.4104 | 0.6667 |
| No log | 3.0 | 159 | 0.2117 | 0.2117 | 0.3422 | 0.5230 | 0.7667 |
| No log | 4.0 | 212 | 0.3250 | 0.3250 | 0.4990 | 0.2677 | 0.55 |
| No log | 5.0 | 265 | 0.2494 | 0.2494 | 0.3321 | 0.4380 | 0.7167 |
| No log | 6.0 | 318 | 0.2477 | 0.2477 | 0.3488 | 0.4419 | 0.75 |
| No log | 7.0 | 371 | 0.3209 | 0.3209 | 0.3599 | 0.2770 | 0.7833 |
| No log | 8.0 | 424 | 0.2704 | 0.2704 | 0.3715 | 0.3909 | 0.7 |
| No log | 9.0 | 477 | 0.2886 | 0.2886 | 0.3185 | 0.3498 | 0.7833 |
| 0.1507 | 10.0 | 530 | 0.2477 | 0.2477 | 0.3071 | 0.4418 | 0.7667 |
| 0.1507 | 11.0 | 583 | 0.2670 | 0.2670 | 0.3232 | 0.3984 | 0.7833 |
| 0.1507 | 12.0 | 636 | 0.2285 | 0.2285 | 0.2926 | 0.4851 | 0.75 |
| 0.1507 | 13.0 | 689 | 0.2378 | 0.2378 | 0.2980 | 0.4643 | 0.7833 |
| 0.1507 | 14.0 | 742 | 0.2544 | 0.2544 | 0.3194 | 0.4269 | 0.7667 |
| 0.1507 | 15.0 | 795 | 0.2571 | 0.2571 | 0.2904 | 0.4208 | 0.8 |
| 0.1507 | 16.0 | 848 | 0.2505 | 0.2505 | 0.2884 | 0.4357 | 0.8 |
| 0.1507 | 17.0 | 901 | 0.2654 | 0.2654 | 0.2846 | 0.4022 | 0.8 |
| 0.1507 | 18.0 | 954 | 0.2606 | 0.2606 | 0.2785 | 0.4128 | 0.8 |
| 0.0203 | 19.0 | 1007 | 0.2519 | 0.2519 | 0.2816 | 0.4324 | 0.8 |
| 0.0203 | 20.0 | 1060 | 0.2634 | 0.2634 | 0.2826 | 0.4065 | 0.8 |
Framework versions
- Transformers 4.27.4
- Pytorch 1.13.1+cu116
- Datasets 2.11.0
- Tokenizers 0.13.2
