distilbert-base-uncased-finetuned-ft1500_norm300
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.0940
- Mse: 4.3760
- Mae: 1.4084
- R2: 0.4625
- Accuracy: 0.3517
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: 2e-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: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | Mse | Mae | R2 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.7424 | 1.0 | 3122 | 1.1071 | 4.4286 | 1.4098 | 0.4561 | 0.3338 |
| 0.5038 | 2.0 | 6244 | 1.1794 | 4.7177 | 1.4140 | 0.4205 | 0.3677 |
| 0.356 | 3.0 | 9366 | 1.0717 | 4.2866 | 1.3852 | 0.4735 | 0.3581 |
| 0.2293 | 4.0 | 12488 | 1.0940 | 4.3760 | 1.4084 | 0.4625 | 0.3517 |
Framework versions
- Transformers 4.21.1
- Pytorch 1.12.0+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1
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