metadata
library_name: transformers
license: mit
base_model: FacebookAI/roberta-large
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: fine_tuned_super_clean_raid
results: []
fine_tuned_super_clean_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: 0.0885
- Accuracy: 0.9715
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 |
|---|---|---|---|---|
| 0.3162 | 0.0196 | 100 | 0.2046 | 0.9306 |
| 0.2626 | 0.0393 | 200 | 0.2988 | 0.9129 |
| 0.2888 | 0.0589 | 300 | 0.2148 | 0.9490 |
| 0.217 | 0.0786 | 400 | 0.1970 | 0.9523 |
| 0.2201 | 0.0982 | 500 | 0.1533 | 0.9596 |
| 0.2836 | 0.1178 | 600 | 0.1406 | 0.9563 |
| 0.2196 | 0.1375 | 700 | 0.1326 | 0.9574 |
| 0.1669 | 0.1571 | 800 | 0.1549 | 0.9622 |
| 0.1482 | 0.1767 | 900 | 0.1740 | 0.9629 |
| 0.1997 | 0.1964 | 1000 | 0.0885 | 0.9715 |
| 0.1271 | 0.2160 | 1100 | 0.4294 | 0.9163 |
| 0.1754 | 0.2357 | 1200 | 0.1268 | 0.9567 |
| 0.1479 | 0.2553 | 1300 | 0.3952 | 0.9328 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3