---
license: mit
base_model: xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: xlm-roberta-base-Final_Mixed-aug_replace_tfidf-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_tfidf-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: 0.7044
- Accuracy: 0.76
- F1: 0.7519

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 1.083         | 1.0   | 88   | 0.9789          | 0.6      | 0.4933 |
| 0.9576        | 2.0   | 176  | 0.7989          | 0.66     | 0.6019 |
| 0.8381        | 3.0   | 264  | 0.8103          | 0.67     | 0.6320 |
| 0.744         | 4.0   | 352  | 0.6355          | 0.74     | 0.7250 |
| 0.6186        | 5.0   | 440  | 0.6820          | 0.77     | 0.7660 |
| 0.5534        | 6.0   | 528  | 0.6782          | 0.76     | 0.7519 |
| 0.4677        | 7.0   | 616  | 0.6447          | 0.79     | 0.7810 |
| 0.4132        | 8.0   | 704  | 0.7044          | 0.76     | 0.7519 |


### Framework versions

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