---
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: 0.8727
- Accuracy: 0.76
- F1: 0.7592

## 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: 41
- 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 1.0219        | 1.0   | 87   | 0.7346          | 0.68     | 0.6276 |
| 0.7518        | 2.0   | 174  | 0.5934          | 0.75     | 0.7425 |
| 0.6023        | 3.0   | 261  | 0.7553          | 0.7      | 0.6975 |
| 0.479         | 4.0   | 348  | 0.7275          | 0.72     | 0.7118 |
| 0.3515        | 5.0   | 435  | 0.9068          | 0.74     | 0.7306 |
| 0.2646        | 6.0   | 522  | 0.7953          | 0.77     | 0.7633 |
| 0.2123        | 7.0   | 609  | 0.8673          | 0.77     | 0.7652 |
| 0.1535        | 8.0   | 696  | 0.8727          | 0.76     | 0.7592 |


### Framework versions

- Transformers 4.33.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3