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distilbert-base-uncased-finetuned-ft1500_norm300_aug5_10_8x_plus_8_10_4x
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: 1.0732
- Mse: 4.2926
- Mae: 1.3756
- R2: 0.4728
- Accuracy: 0.3427
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: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Mse | Mae | R2 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.7013 | 1.0 | 7652 | 1.0583 | 4.2330 | 1.5178 | 0.4801 | 0.2056 |
| 0.3648 | 2.0 | 15304 | 1.0732 | 4.2926 | 1.3756 | 0.4728 | 0.3427 |
Framework versions
- Transformers 4.21.1
- Pytorch 1.12.1+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1
