transformers pytorch xlm-roberta text-classification generated_from_trainer base_model:FacebookAI/xlm-roberta-base base_model:finetune:FacebookAI/xlm-roberta-base license:mit autotrain_compatible endpoints_compatible region:us
---
base_model: xlm-roberta-base
license: mit
metrics:
- accuracy
- f1
tags:
- generated_from_trainer
model-index:
- name: xlm-roberta-base-Final_Mixed-aug_backtranslation-2
  results: []
---

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# xlm-roberta-base-Final_Mixed-aug_backtranslation-2

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: 1.1103
- Accuracy: 0.74
- F1: 0.7315

## 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: 40
- 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 1.0442        | 1.0   | 87   | 0.7191          | 0.69     | 0.6652 |
| 0.7545        | 2.0   | 174  | 0.6726          | 0.73     | 0.7264 |
| 0.5743        | 3.0   | 261  | 0.6634          | 0.72     | 0.7157 |
| 0.4342        | 4.0   | 348  | 0.7801          | 0.73     | 0.7270 |
| 0.3244        | 5.0   | 435  | 0.8782          | 0.75     | 0.7438 |
| 0.2421        | 6.0   | 522  | 1.0173          | 0.73     | 0.7235 |
| 0.167         | 7.0   | 609  | 1.0822          | 0.75     | 0.7431 |
| 0.1546        | 8.0   | 696  | 1.1103          | 0.74     | 0.7315 |


### Framework versions

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