---
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: roberta-base
  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. -->

# roberta-base

This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3752
- Accuracy: 0.8436
- Precision: 0.8472
- Recall: 0.8383
- F1: 0.8427

## 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: 1e-05
- train_batch_size: 32
- eval_batch_size: 32
- 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 | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.5737        | 1.0   | 1074 | 0.4409          | 0.8018   | 0.8208    | 0.7723 | 0.7958 |
| 0.3689        | 2.0   | 2148 | 0.3821          | 0.8304   | 0.8398    | 0.8165 | 0.8280 |
| 0.3038        | 3.0   | 3222 | 0.3752          | 0.8436   | 0.8472    | 0.8383 | 0.8427 |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0