<!-- 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. -->
bert-base-uncased-finetuned-classification
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: 38.9115
- Mse: 38.9115
- Mae: 4.5330
- R2: 0.7802
- Accuracy: 0.1620
- Msev: 0.0257
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 |
|---|---|---|---|---|---|---|---|---|
| 12.4524 | 1.0 | 5215 | 43.9797 | 43.9797 | 4.8194 | 0.7515 | 0.1693 | 0.0227 |
| 4.393 | 2.0 | 10430 | 39.2333 | 39.2333 | 4.6028 | 0.7783 | 0.1737 | 0.0255 |
| 2.424 | 3.0 | 15645 | 41.3763 | 41.3763 | 4.6597 | 0.7662 | 0.1620 | 0.0242 |
| 1.781 | 4.0 | 20860 | 39.4309 | 39.4309 | 4.5960 | 0.7772 | 0.1767 | 0.0254 |
| 1.3608 | 5.0 | 26075 | 38.9115 | 38.9115 | 4.5330 | 0.7802 | 0.1620 | 0.0257 |
| 1.2014 | 6.0 | 31290 | 39.7403 | 39.7403 | 4.5850 | 0.7755 | 0.1716 | 0.0252 |
| 1.0742 | 7.0 | 36505 | 40.4495 | 40.4495 | 4.6133 | 0.7715 | 0.1685 | 0.0247 |
| 0.837 | 8.0 | 41720 | 39.5864 | 39.5864 | 4.5630 | 0.7763 | 0.1620 | 0.0253 |
| 0.8054 | 9.0 | 46935 | 39.9482 | 39.9482 | 4.5839 | 0.7743 | 0.1569 | 0.0250 |
| 0.8085 | 10.0 | 52150 | 39.5685 | 39.5685 | 4.5669 | 0.7764 | 0.1573 | 0.0253 |
Framework versions
- Transformers 4.21.3
- Pytorch 1.12.1+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1
