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bert-base-uncased-finetuned-classification_TokenNew
This model is a fine-tuned version of bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 41.4553
- Mse: 41.4553
- Mae: 4.7280
- R2: 0.7658
- Accuracy: 0.1600
- Msev: 0.0241
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Mse | Mae | R2 | Accuracy | Msev |
|---|---|---|---|---|---|---|---|---|
| 10.3178 | 1.0 | 5215 | 41.8852 | 41.8852 | 4.6705 | 0.7634 | 0.1827 | 0.0239 |
| 3.6731 | 2.0 | 10430 | 45.6101 | 45.6101 | 4.9092 | 0.7423 | 0.1809 | 0.0219 |
| 2.0891 | 3.0 | 15645 | 42.1319 | 42.1319 | 4.7640 | 0.7620 | 0.1525 | 0.0237 |
| 1.5213 | 4.0 | 20860 | 42.0646 | 42.0646 | 4.7562 | 0.7623 | 0.1588 | 0.0238 |
| 1.1904 | 5.0 | 26075 | 42.0155 | 42.0155 | 4.7778 | 0.7626 | 0.1563 | 0.0238 |
| 1.0127 | 6.0 | 31290 | 41.6389 | 41.6389 | 4.7342 | 0.7647 | 0.1660 | 0.0240 |
| 0.9218 | 7.0 | 36505 | 40.9860 | 40.9860 | 4.7009 | 0.7684 | 0.1589 | 0.0244 |
| 0.7466 | 8.0 | 41720 | 40.1809 | 40.1809 | 4.6686 | 0.7730 | 0.1629 | 0.0249 |
| 0.7264 | 9.0 | 46935 | 40.9795 | 40.9795 | 4.7043 | 0.7685 | 0.1616 | 0.0244 |
| 0.6968 | 10.0 | 52150 | 41.4553 | 41.4553 | 4.7280 | 0.7658 | 0.1600 | 0.0241 |
Framework versions
- Transformers 4.21.3
- Pytorch 1.12.1+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1
