---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: roberta-base
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# roberta-base

This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1585
- Accuracy: 0.9762

## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.2838        | 1.0   | 3492  | 0.2001          | 0.9628   |
| 0.1463        | 2.0   | 6984  | 0.1663          | 0.9725   |
| 0.0922        | 3.0   | 10476 | 0.1962          | 0.9728   |
| 0.081         | 4.0   | 13968 | 0.1684          | 0.9725   |
| 0.0487        | 5.0   | 17460 | 0.1585          | 0.9762   |
| 0.0443        | 6.0   | 20952 | 0.1707          | 0.9762   |
| 0.0216        | 7.0   | 24444 | 0.1984          | 0.9765   |
| 0.0341        | 8.0   | 27936 | 0.1892          | 0.9751   |


### Framework versions

- Transformers 4.28.0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3