---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: finetuned_roberta-base-uncased
  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. -->

# finetuned_roberta-base-uncased

This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4799
- Accuracy: 0.6519

## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.372         | 1.0   | 102  | 1.3643          | 0.3375   |
| 1.1591        | 2.0   | 204  | 1.1988          | 0.4830   |
| 0.9623        | 3.0   | 306  | 1.0802          | 0.5694   |
| 0.7766        | 4.0   | 408  | 0.9885          | 0.6237   |
| 0.7336        | 5.0   | 510  | 1.0393          | 0.6120   |
| 0.6284        | 6.0   | 612  | 1.1150          | 0.6392   |
| 0.3616        | 7.0   | 714  | 1.2183          | 0.6402   |
| 0.3526        | 8.0   | 816  | 1.2362          | 0.6305   |
| 0.3151        | 9.0   | 918  | 1.3058          | 0.6372   |
| 0.3035        | 10.0  | 1020 | 1.2966          | 0.6343   |
| 0.2458        | 11.0  | 1122 | 1.3752          | 0.6508   |
| 0.2469        | 12.0  | 1224 | 1.4557          | 0.6557   |
| 0.2039        | 13.0  | 1326 | 1.5541          | 0.6372   |
| 0.1691        | 14.0  | 1428 | 1.5308          | 0.6343   |
| 0.1455        | 15.0  | 1530 | 1.6339          | 0.6421   |
| 0.1716        | 16.0  | 1632 | 1.6843          | 0.6392   |
| 0.1698        | 17.0  | 1734 | 1.6802          | 0.6479   |
| 0.2009        | 18.0  | 1836 | 1.6544          | 0.6479   |
| 0.1415        | 19.0  | 1938 | 1.6759          | 0.6518   |
| 0.1616        | 20.0  | 2040 | 1.6833          | 0.6508   |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2