bert-base-uncased-2-finetuned-RRamicus
This model is a fine-tuned version of bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.4784
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: 8
- eval_batch_size: 8
- seed: 928
- 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 |
|---|---|---|---|
| 2.0341 | 1.0 | 1113 | 1.7515 |
| 1.7881 | 2.0 | 2226 | 1.6616 |
| 1.697 | 3.0 | 3339 | 1.6061 |
| 1.6328 | 4.0 | 4452 | 1.5662 |
| 1.5919 | 5.0 | 5565 | 1.5362 |
| 1.5602 | 6.0 | 6678 | 1.5193 |
| 1.5221 | 7.0 | 7791 | 1.4984 |
| 1.5135 | 8.0 | 8904 | 1.4898 |
| 1.4917 | 9.0 | 10017 | 1.4755 |
| 1.4859 | 10.0 | 11130 | 1.4671 |
Framework versions
- Transformers 4.18.0
- Pytorch 1.10.0+cu111
- Datasets 2.1.0
- Tokenizers 0.12.1
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