---
license: mit
base_model: xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: xlm-roberta-base-Mixed-aug_insert_vi
  results: []
---

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

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: 0.5693
- Accuracy: 0.81
- F1: 0.7858

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.9098        | 1.0   | 82   | 0.6306          | 0.75     | 0.7083 |
| 0.6867        | 2.0   | 164  | 0.7511          | 0.77     | 0.7175 |
| 0.5754        | 3.0   | 246  | 0.5041          | 0.82     | 0.7719 |
| 0.4309        | 4.0   | 328  | 0.5971          | 0.8      | 0.7754 |
| 0.3739        | 5.0   | 410  | 0.5693          | 0.81     | 0.7858 |


### Framework versions

- Transformers 4.32.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3