---
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: 0.0505
- Accuracy: 0.9905

## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.2402        | 0.04  | 100  | 0.1240          | 0.961    |
| 0.1607        | 0.09  | 200  | 0.1677          | 0.9765   |
| 0.1589        | 0.13  | 300  | 0.0773          | 0.983    |
| 0.0966        | 0.18  | 400  | 0.0812          | 0.986    |
| 0.0916        | 0.22  | 500  | 0.0965          | 0.9835   |
| 0.0922        | 0.27  | 600  | 0.0745          | 0.986    |
| 0.0338        | 0.31  | 700  | 0.0745          | 0.9895   |
| 0.1024        | 0.36  | 800  | 0.0807          | 0.9835   |
| 0.0984        | 0.4   | 900  | 0.1363          | 0.9805   |
| 0.0644        | 0.44  | 1000 | 0.0505          | 0.9905   |
| 0.0582        | 0.49  | 1100 | 0.1026          | 0.9835   |
| 0.038         | 0.53  | 1200 | 0.0535          | 0.992    |
| 0.0554        | 0.58  | 1300 | 0.0566          | 0.991    |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.1+cu118
- Datasets 2.16.0
- Tokenizers 0.15.0