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

# fine_tuned_rte_XLMroberta

This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4763
- Accuracy: 0.6207
- F1: 0.5951

## 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
- training_steps: 400

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-------:|:----:|:---------------:|:--------:|:------:|
| 0.7117        | 1.7241  | 50   | 0.7129          | 0.4138   | 0.2422 |
| 0.7033        | 3.4483  | 100  | 0.6997          | 0.4138   | 0.2422 |
| 0.6845        | 5.1724  | 150  | 0.6933          | 0.4828   | 0.4828 |
| 0.6378        | 6.8966  | 200  | 0.8005          | 0.4828   | 0.4668 |
| 0.4579        | 8.6207  | 250  | 0.9656          | 0.6207   | 0.5951 |
| 0.2521        | 10.3448 | 300  | 1.2302          | 0.6552   | 0.6018 |
| 0.1196        | 12.0690 | 350  | 1.4679          | 0.5862   | 0.5789 |
| 0.0653        | 13.7931 | 400  | 1.4763          | 0.6207   | 0.5951 |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.1.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1