---
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: []
---

<!-- 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_super_clean_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: 0.0885
- 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