---
license: mit
base_model: xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: xlm-roberta-base-Final_Mixed-aug_replace_synonym-1
  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. -->

# xlm-roberta-base-Final_Mixed-aug_replace_synonym-1

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: 0.9852
- Accuracy: 0.74
- F1: 0.7369

## 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: 8

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 1.0471        | 1.0   | 87   | 0.9289          | 0.64     | 0.5512 |
| 0.9553        | 2.0   | 174  | 0.7912          | 0.64     | 0.5672 |
| 0.7049        | 3.0   | 261  | 0.6276          | 0.75     | 0.7341 |
| 0.5556        | 4.0   | 348  | 0.7291          | 0.74     | 0.7291 |
| 0.435         | 5.0   | 435  | 0.6930          | 0.72     | 0.7163 |
| 0.3534        | 6.0   | 522  | 0.8526          | 0.74     | 0.7369 |
| 0.2774        | 7.0   | 609  | 0.9620          | 0.73     | 0.7259 |
| 0.2152        | 8.0   | 696  | 0.9852          | 0.74     | 0.7369 |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3