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bert-base-uncased-finetuned-classification_ds30
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: 41.1515
- Mse: 41.1515
- Mae: 4.7002
- R2: 0.7675
- Accuracy: 0.2685
- Msev: 0.0243
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 |
|---|---|---|---|---|---|---|---|---|
| 10.1514 | 1.0 | 5215 | 40.1844 | 40.1844 | 4.6065 | 0.7730 | 0.2644 | 0.0249 |
| 3.7754 | 2.0 | 10430 | 39.4067 | 39.4067 | 4.5926 | 0.7774 | 0.2803 | 0.0254 |
| 2.2314 | 3.0 | 15645 | 44.9527 | 44.9527 | 4.8825 | 0.7460 | 0.2680 | 0.0222 |
| 1.6468 | 4.0 | 20860 | 40.3435 | 40.3435 | 4.6496 | 0.7721 | 0.2702 | 0.0248 |
| 1.2442 | 5.0 | 26075 | 40.8178 | 40.8178 | 4.6934 | 0.7694 | 0.2657 | 0.0245 |
| 1.0992 | 6.0 | 31290 | 42.6644 | 42.6644 | 4.7802 | 0.7590 | 0.2620 | 0.0234 |
| 0.9911 | 7.0 | 36505 | 40.0627 | 40.0627 | 4.6277 | 0.7737 | 0.2751 | 0.0250 |
| 0.8167 | 8.0 | 41720 | 40.6918 | 40.6918 | 4.6755 | 0.7701 | 0.2693 | 0.0246 |
| 0.7862 | 9.0 | 46935 | 41.9593 | 41.9593 | 4.7363 | 0.7629 | 0.2693 | 0.0238 |
| 0.8136 | 10.0 | 52150 | 41.1515 | 41.1515 | 4.7002 | 0.7675 | 0.2685 | 0.0243 |
Framework versions
- Transformers 4.22.0
- Pytorch 1.12.1+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1
