<!-- 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_11_aug
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: 0.2285
- Mse: 0.2285
- Mae: 0.3670
- R2: 0.4927
- Accuracy: 0.7067
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 | 263 | 0.2010 | 0.2010 | 0.3575 | 0.5311 | 0.7367 |
| 0.2435 | 2.0 | 526 | 0.1490 | 0.1490 | 0.2495 | 0.6523 | 0.8733 |
| 0.2435 | 3.0 | 789 | 0.0972 | 0.0972 | 0.2068 | 0.7732 | 0.9067 |
| 0.0906 | 4.0 | 1052 | 0.1115 | 0.1115 | 0.2082 | 0.7399 | 0.9067 |
| 0.0906 | 5.0 | 1315 | 0.0904 | 0.0904 | 0.1684 | 0.7890 | 0.9 |
| 0.0421 | 6.0 | 1578 | 0.0791 | 0.0791 | 0.1542 | 0.8153 | 0.93 |
| 0.0421 | 7.0 | 1841 | 0.0843 | 0.0843 | 0.1415 | 0.8034 | 0.9133 |
| 0.0274 | 8.0 | 2104 | 0.0694 | 0.0694 | 0.1152 | 0.8380 | 0.9333 |
| 0.0274 | 9.0 | 2367 | 0.0742 | 0.0742 | 0.1435 | 0.8269 | 0.93 |
| 0.0213 | 10.0 | 2630 | 0.0659 | 0.0659 | 0.1022 | 0.8463 | 0.9367 |
| 0.0213 | 11.0 | 2893 | 0.0600 | 0.0600 | 0.1054 | 0.8599 | 0.9433 |
| 0.0127 | 12.0 | 3156 | 0.0540 | 0.0540 | 0.0988 | 0.8739 | 0.9433 |
| 0.0127 | 13.0 | 3419 | 0.0479 | 0.0479 | 0.0854 | 0.8883 | 0.9567 |
| 0.0077 | 14.0 | 3682 | 0.0517 | 0.0517 | 0.0848 | 0.8793 | 0.95 |
| 0.0077 | 15.0 | 3945 | 0.0405 | 0.0405 | 0.0851 | 0.9054 | 0.9633 |
| 0.0051 | 16.0 | 4208 | 0.0430 | 0.0430 | 0.0742 | 0.8996 | 0.9533 |
| 0.0051 | 17.0 | 4471 | 0.0368 | 0.0368 | 0.0721 | 0.9142 | 0.96 |
| 0.0036 | 18.0 | 4734 | 0.0352 | 0.0352 | 0.0709 | 0.9180 | 0.96 |
| 0.0036 | 19.0 | 4997 | 0.0345 | 0.0345 | 0.0654 | 0.9195 | 0.9567 |
| 0.0029 | 20.0 | 5260 | 0.0366 | 0.0366 | 0.0671 | 0.9146 | 0.96 |
Framework versions
- Transformers 4.27.4
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3
