---
license: mit
base_model: xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: xlm-roberta-base-Balance_Mixed-aug_backtranslation
  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-Balance_Mixed-aug_backtranslation

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: 1.4382
- Accuracy: 0.72
- F1: 0.7219

## 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: 8
- eval_batch_size: 8
- 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.9831        | 1.0   | 174  | 0.9044          | 0.61     | 0.5474 |
| 0.7797        | 2.0   | 348  | 0.6469          | 0.73     | 0.7378 |
| 0.6314        | 3.0   | 522  | 0.6261          | 0.76     | 0.7619 |
| 0.4976        | 4.0   | 696  | 0.8230          | 0.72     | 0.7177 |
| 0.3719        | 5.0   | 870  | 1.0086          | 0.72     | 0.7223 |
| 0.2816        | 6.0   | 1044 | 1.3198          | 0.72     | 0.7208 |
| 0.2772        | 7.0   | 1218 | 1.3510          | 0.71     | 0.7099 |
| 0.2076        | 8.0   | 1392 | 1.4382          | 0.72     | 0.7219 |


### Framework versions

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