---
library_name: transformers
license: mit
base_model: FacebookAI/roberta-large
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: fine_tuned_main_raid
  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

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: 0.0407
- Accuracy: 0.9922

## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.3543        | 0.0767 | 100  | 0.1765          | 0.9655   |
| 0.1516        | 0.1534 | 200  | 0.1955          | 0.9724   |
| 0.1415        | 0.2301 | 300  | 0.1323          | 0.9724   |
| 0.2002        | 0.3067 | 400  | 0.0993          | 0.9716   |
| 0.1057        | 0.3834 | 500  | 0.2031          | 0.9552   |
| 0.0734        | 0.4601 | 600  | 0.1010          | 0.9802   |
| 0.0725        | 0.5368 | 700  | 0.1511          | 0.9767   |
| 0.1326        | 0.6135 | 800  | 0.0607          | 0.9879   |
| 0.0667        | 0.6902 | 900  | 0.0734          | 0.9845   |
| 0.1132        | 0.7669 | 1000 | 0.0878          | 0.9819   |
| 0.0731        | 0.8436 | 1100 | 0.0694          | 0.9888   |
| 0.0678        | 0.9202 | 1200 | 0.0704          | 0.9853   |
| 0.0455        | 0.9969 | 1300 | 0.0522          | 0.9905   |
| 0.0656        | 1.0736 | 1400 | 0.0646          | 0.9871   |
| 0.0463        | 1.1503 | 1500 | 0.0407          | 0.9922   |
| 0.0432        | 1.2270 | 1600 | 0.0646          | 0.9897   |
| 0.0347        | 1.3037 | 1700 | 0.0421          | 0.9931   |
| 0.0361        | 1.3804 | 1800 | 0.0420          | 0.9931   |


### Framework versions

- Transformers 4.46.2
- Pytorch 2.5.0+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3