roberta-large-phatic-2
This model is a fine-tuned version of FacebookAI/roberta-large on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1169
- Accuracy: 0.9822
- Precision: 0.9643
- Recall: 1.0
- F1: 0.9818
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: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 6
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 0.5143 | 1.0 | 74 | 0.3871 | 0.8639 | 0.8816 | 0.8272 | 0.8535 |
| 0.3971 | 2.0 | 148 | 0.2456 | 0.9172 | 0.8602 | 0.9877 | 0.9195 |
| 0.1915 | 3.0 | 222 | 0.1843 | 0.9645 | 0.9518 | 0.9753 | 0.9634 |
| 0.0863 | 4.0 | 296 | 0.2293 | 0.9586 | 0.9205 | 1.0 | 0.9586 |
| 0.2564 | 5.0 | 370 | 0.0819 | 0.9763 | 0.9639 | 0.9877 | 0.9756 |
| 0.0002 | 6.0 | 444 | 0.1169 | 0.9822 | 0.9643 | 1.0 | 0.9818 |
Framework versions
- Transformers 4.50.0
- Pytorch 2.3.0+cu118
- Datasets 2.21.0
- Tokenizers 0.21.1
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Model tree for rocker417/roberta-large-phatic-2
Base model
FacebookAI/roberta-large