---
library_name: transformers
license: mit
base_model: FacebookAI/roberta-large
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: fine_tuned_main_raid_cleaned
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# fine_tuned_main_raid_cleaned

This model is a fine-tuned version of [FacebookAI/roberta-large](https://huggingface.co/FacebookAI/roberta-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0545
- Accuracy: 0.9863

## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.4795        | 0.1018 | 100  | 0.1646          | 0.9680   |
| 0.2962        | 0.2037 | 200  | 0.3051          | 0.9451   |
| 0.145         | 0.3055 | 300  | 0.0977          | 0.9783   |
| 0.1013        | 0.4073 | 400  | 0.0962          | 0.9794   |
| 0.1147        | 0.5092 | 500  | 0.1666          | 0.9657   |
| 0.1772        | 0.6110 | 600  | 0.1542          | 0.9691   |
| 0.1423        | 0.7128 | 700  | 0.0671          | 0.9851   |
| 0.0614        | 0.8147 | 800  | 0.0869          | 0.9840   |
| 0.0935        | 0.9165 | 900  | 0.0599          | 0.9863   |
| 0.0608        | 1.0183 | 1000 | 0.1149          | 0.9805   |
| 0.0233        | 1.1202 | 1100 | 0.1006          | 0.9851   |
| 0.0825        | 1.2220 | 1200 | 0.3549          | 0.9359   |
| 0.0363        | 1.3238 | 1300 | 0.0660          | 0.9886   |
| 0.0411        | 1.4257 | 1400 | 0.1984          | 0.9737   |
| 0.0648        | 1.5275 | 1500 | 0.0545          | 0.9863   |
| 0.0483        | 1.6293 | 1600 | 0.0737          | 0.9886   |
| 0.0256        | 1.7312 | 1700 | 0.1071          | 0.9851   |
| 0.0195        | 1.8330 | 1800 | 0.1365          | 0.9805   |


### Framework versions

- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3