<!-- 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_8
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: 0.0710
- Mse: 0.0710
- Mae: 0.1978
- R2: 0.0202
- Accuracy: 0.9259
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 | 49 | 0.0777 | 0.0777 | 0.2323 | 0.2804 | 0.9464 |
| No log | 2.0 | 98 | 0.0649 | 0.0649 | 0.2176 | 0.3990 | 0.9464 |
| No log | 3.0 | 147 | 0.0885 | 0.0885 | 0.2354 | 0.1799 | 0.8571 |
| No log | 4.0 | 196 | 0.0620 | 0.0620 | 0.1971 | 0.4252 | 0.9643 |
| No log | 5.0 | 245 | 0.0605 | 0.0605 | 0.2071 | 0.4394 | 0.9821 |
| No log | 6.0 | 294 | 0.0523 | 0.0523 | 0.1714 | 0.5155 | 0.9821 |
| No log | 7.0 | 343 | 0.1047 | 0.1047 | 0.2598 | 0.0301 | 0.8393 |
| No log | 8.0 | 392 | 0.0421 | 0.0421 | 0.1543 | 0.6103 | 0.9643 |
| No log | 9.0 | 441 | 0.0445 | 0.0445 | 0.1612 | 0.5875 | 0.9643 |
| No log | 10.0 | 490 | 0.0438 | 0.0438 | 0.1608 | 0.5939 | 0.9821 |
| 0.0478 | 11.0 | 539 | 0.0529 | 0.0529 | 0.1816 | 0.5095 | 0.9464 |
| 0.0478 | 12.0 | 588 | 0.0401 | 0.0401 | 0.1495 | 0.6288 | 0.9643 |
| 0.0478 | 13.0 | 637 | 0.0471 | 0.0471 | 0.1637 | 0.5639 | 0.9643 |
| 0.0478 | 14.0 | 686 | 0.0454 | 0.0454 | 0.1632 | 0.5797 | 0.9643 |
| 0.0478 | 15.0 | 735 | 0.0436 | 0.0436 | 0.1526 | 0.5957 | 0.9643 |
| 0.0478 | 16.0 | 784 | 0.0520 | 0.0520 | 0.1764 | 0.5178 | 0.9643 |
| 0.0478 | 17.0 | 833 | 0.0414 | 0.0414 | 0.1536 | 0.6166 | 0.9821 |
| 0.0478 | 18.0 | 882 | 0.0413 | 0.0413 | 0.1490 | 0.6176 | 0.9643 |
| 0.0478 | 19.0 | 931 | 0.0413 | 0.0413 | 0.1514 | 0.6174 | 0.9821 |
| 0.0478 | 20.0 | 980 | 0.0429 | 0.0429 | 0.1537 | 0.6023 | 0.9821 |
Framework versions
- Transformers 4.27.3
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2
