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Regression_Albert
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: 0.0459
- Mse: 0.0459
- Mae: 0.1675
- R2: 0.9763
- Accuracy: 1.0
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: 1e-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: 25
Training results
| Training Loss | Epoch | Step | Validation Loss | Mse | Mae | R2 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 7 | 1.4379 | 1.4379 | 1.1107 | -0.3492 | 0.0 |
| No log | 2.0 | 14 | 1.2159 | 1.2159 | 1.0476 | -0.1409 | 0.1429 |
| No log | 3.0 | 21 | 1.7679 | 1.7679 | 1.1233 | -0.6588 | 0.4286 |
| No log | 4.0 | 28 | 1.7069 | 1.7069 | 1.1072 | -0.6015 | 0.1429 |
| No log | 5.0 | 35 | 1.4438 | 1.4438 | 0.9771 | -0.3547 | 0.5714 |
| No log | 6.0 | 42 | 1.0275 | 1.0275 | 0.7910 | 0.0359 | 0.4286 |
| No log | 7.0 | 49 | 0.7649 | 0.7649 | 0.7080 | 0.2823 | 0.4286 |
| No log | 8.0 | 56 | 0.6584 | 0.6584 | 0.7083 | 0.3823 | 0.2857 |
| No log | 9.0 | 63 | 0.5064 | 0.5064 | 0.6108 | 0.5248 | 0.4286 |
| No log | 10.0 | 70 | 0.3638 | 0.3638 | 0.5078 | 0.6586 | 0.4286 |
| No log | 11.0 | 77 | 0.2660 | 0.2660 | 0.4352 | 0.7504 | 0.5714 |
| No log | 12.0 | 84 | 0.1570 | 0.1570 | 0.3323 | 0.8527 | 0.7143 |
| No log | 13.0 | 91 | 0.1953 | 0.1953 | 0.3863 | 0.8168 | 0.4286 |
| No log | 14.0 | 98 | 0.2230 | 0.2230 | 0.4033 | 0.7908 | 0.7143 |
| No log | 15.0 | 105 | 0.0578 | 0.0578 | 0.1935 | 0.9458 | 1.0 |
| No log | 16.0 | 112 | 0.0504 | 0.0504 | 0.1701 | 0.9527 | 1.0 |
| No log | 17.0 | 119 | 0.0466 | 0.0466 | 0.1713 | 0.9563 | 1.0 |
| No log | 18.0 | 126 | 0.0173 | 0.0173 | 0.1148 | 0.9837 | 1.0 |
| No log | 19.0 | 133 | 0.0417 | 0.0417 | 0.1811 | 0.9609 | 1.0 |
| No log | 20.0 | 140 | 0.0899 | 0.0899 | 0.1895 | 0.9156 | 0.8571 |
| No log | 21.0 | 147 | 0.0571 | 0.0571 | 0.1599 | 0.9465 | 0.8571 |
| No log | 22.0 | 154 | 0.0247 | 0.0247 | 0.1478 | 0.9768 | 1.0 |
| No log | 23.0 | 161 | 0.0201 | 0.0201 | 0.1261 | 0.9812 | 1.0 |
| No log | 24.0 | 168 | 0.0178 | 0.0178 | 0.1262 | 0.9833 | 1.0 |
| No log | 25.0 | 175 | 0.0172 | 0.0172 | 0.1208 | 0.9838 | 1.0 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2
