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Regression_xlnet_NOaug_MSEloss
This model is a fine-tuned version of xlnet-base-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6460
- Mse: 0.6460
- Mae: 0.7041
- R2: -0.1893
- Accuracy: 0.2632
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-12
- 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: 15
Training results
| Training Loss | Epoch | Step | Validation Loss | Mse | Mae | R2 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 33 | 0.7342 | 0.7342 | 0.7706 | -1.1938 | 0.2703 |
| No log | 2.0 | 66 | 0.7342 | 0.7342 | 0.7706 | -1.1938 | 0.2703 |
| No log | 3.0 | 99 | 0.7342 | 0.7342 | 0.7706 | -1.1938 | 0.2703 |
| No log | 4.0 | 132 | 0.7342 | 0.7342 | 0.7706 | -1.1938 | 0.2703 |
| No log | 5.0 | 165 | 0.7342 | 0.7342 | 0.7706 | -1.1938 | 0.2703 |
| No log | 6.0 | 198 | 0.7342 | 0.7342 | 0.7706 | -1.1938 | 0.2703 |
| No log | 7.0 | 231 | 0.7342 | 0.7342 | 0.7706 | -1.1938 | 0.2703 |
| No log | 8.0 | 264 | 0.7342 | 0.7342 | 0.7706 | -1.1938 | 0.2703 |
| No log | 9.0 | 297 | 0.7342 | 0.7342 | 0.7706 | -1.1938 | 0.2703 |
| No log | 10.0 | 330 | 0.7342 | 0.7342 | 0.7706 | -1.1938 | 0.2703 |
| No log | 11.0 | 363 | 0.7342 | 0.7342 | 0.7706 | -1.1938 | 0.2703 |
| No log | 12.0 | 396 | 0.7342 | 0.7342 | 0.7706 | -1.1938 | 0.2703 |
| No log | 13.0 | 429 | 0.7342 | 0.7342 | 0.7706 | -1.1938 | 0.2703 |
| No log | 14.0 | 462 | 0.7342 | 0.7342 | 0.7706 | -1.1938 | 0.2703 |
| No log | 15.0 | 495 | 0.7342 | 0.7342 | 0.7706 | -1.1938 | 0.2703 |
Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
