metadata
library_name: transformers
license: mit
base_model: FacebookAI/roberta-large
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: fine_tuned_raid_cleaned
results: []
fine_tuned_raid_cleaned
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: 0.1136
- Accuracy: 0.9800
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: 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: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.3826 | 0.0139 | 100 | 0.1739 | 0.9443 |
| 0.2556 | 0.0277 | 200 | 0.2700 | 0.9408 |
| 0.3383 | 0.0416 | 300 | 0.1667 | 0.9529 |
| 0.3672 | 0.0554 | 400 | 0.9354 | 0.7975 |
| 0.2223 | 0.0693 | 500 | 0.1584 | 0.9673 |
| 0.2197 | 0.0832 | 600 | 0.6363 | 0.8793 |
| 0.2873 | 0.0970 | 700 | 0.2169 | 0.9462 |
| 0.2201 | 0.1109 | 800 | 0.1366 | 0.9621 |
| 0.1695 | 0.1248 | 900 | 0.2912 | 0.9554 |
| 0.1912 | 0.1386 | 1000 | 0.2287 | 0.9542 |
| 0.131 | 0.1525 | 1100 | 0.1136 | 0.9800 |
| 0.1764 | 0.1663 | 1200 | 0.1770 | 0.9645 |
| 0.1195 | 0.1802 | 1300 | 0.1255 | 0.9755 |
| 0.09 | 0.1941 | 1400 | 0.1285 | 0.9758 |
Framework versions
- Transformers 4.46.2
- Pytorch 2.5.0+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3