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roberta-base-finetuned-OIG-mod-2
This model is a fine-tuned version of roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4275
- F1: 0.8487
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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|---|---|---|---|---|
| 0.7205 | 0.36 | 5000 | 0.6986 | 0.7007 |
| 0.6821 | 0.71 | 10000 | 0.6765 | 0.6998 |
| 0.6114 | 1.07 | 15000 | 0.6385 | 0.7281 |
| 0.5854 | 1.42 | 20000 | 0.6077 | 0.7404 |
| 0.5726 | 1.78 | 25000 | 0.5842 | 0.7572 |
| 0.4938 | 2.13 | 30000 | 0.5740 | 0.7722 |
| 0.4752 | 2.49 | 35000 | 0.5379 | 0.7847 |
| 0.473 | 2.84 | 40000 | 0.5139 | 0.7976 |
| 0.4042 | 3.2 | 45000 | 0.4977 | 0.8106 |
| 0.3909 | 3.55 | 50000 | 0.4783 | 0.8199 |
| 0.3779 | 3.91 | 55000 | 0.4507 | 0.8352 |
| 0.3341 | 4.26 | 60000 | 0.4542 | 0.8365 |
| 0.3202 | 4.62 | 65000 | 0.4333 | 0.8465 |
| 0.3101 | 4.97 | 70000 | 0.4275 | 0.8487 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2
