distilbert-base-uncased-finetuned-ft1500_norm500_aug5
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: 0.8927
- Mse: 2.9755
- Mae: 1.0176
- R2: 0.4184
- Accuracy: 0.5003
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: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Mse | Mae | R2 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.4176 | 1.0 | 3952 | 1.0499 | 3.4996 | 1.0853 | 0.3160 | 0.4593 |
| 0.3196 | 2.0 | 7904 | 0.8670 | 2.8901 | 1.0503 | 0.4351 | 0.4600 |
| 0.2084 | 3.0 | 11856 | 0.8927 | 2.9755 | 1.0176 | 0.4184 | 0.5003 |
Framework versions
- Transformers 4.21.1
- Pytorch 1.12.0+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1
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