metadata
library_name: transformers
license: mit
base_model: FacebookAI/roberta-large
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: fine_tuned_main_raid
results: []
fine_tuned_main_raid
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: 0.0711
- Accuracy: 0.9843
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 |
|---|---|---|---|---|
| 0.2533 | 0.0139 | 100 | 0.1743 | 0.9663 |
| 0.1848 | 0.0277 | 200 | 0.1058 | 0.9768 |
| 0.1832 | 0.0416 | 300 | 0.0924 | 0.9796 |
| 0.1199 | 0.0554 | 400 | 0.0854 | 0.9813 |
| 0.1294 | 0.0693 | 500 | 0.2504 | 0.9471 |
| 0.1755 | 0.0832 | 600 | 0.1885 | 0.9646 |
| 0.0831 | 0.0970 | 700 | 0.0831 | 0.9855 |
| 0.1051 | 0.1109 | 800 | 0.0711 | 0.9843 |
| 0.1411 | 0.1248 | 900 | 0.2770 | 0.9637 |
| 0.0761 | 0.1386 | 1000 | 0.0922 | 0.9835 |
| 0.1178 | 0.1525 | 1100 | 0.2174 | 0.9649 |
Framework versions
- Transformers 4.46.2
- Pytorch 2.5.0+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3