---
license: mit
base_model: FacebookAI/roberta-large
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: super_clean_model
  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. -->

# super_clean_model

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: 0.2385
- Accuracy: 0.9485

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6712        | 0.04  | 100  | 0.7864          | 0.6115   |
| 0.4785        | 0.09  | 200  | 1.1828          | 0.7385   |
| 0.475         | 0.13  | 300  | 0.3719          | 0.888    |
| 0.3643        | 0.18  | 400  | 0.6170          | 0.887    |
| 0.3546        | 0.22  | 500  | 0.6397          | 0.9045   |
| 0.3796        | 0.27  | 600  | 0.2512          | 0.9435   |
| 0.3301        | 0.31  | 700  | 0.2626          | 0.9135   |
| 0.3343        | 0.36  | 800  | 0.4675          | 0.8745   |
| 0.3578        | 0.4   | 900  | 0.2701          | 0.903    |
| 0.2604        | 0.44  | 1000 | 0.2385          | 0.9485   |
| 0.3236        | 0.49  | 1100 | 1.9438          | 0.6565   |
| 0.3147        | 0.53  | 1200 | 1.2576          | 0.779    |
| 0.2758        | 0.58  | 1300 | 0.3486          | 0.9345   |


### Framework versions

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