---
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: 1.9629
- Accuracy: 0.5517
- F1: 0.5539

## 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     |
|:-------------:|:-------:|:----:|:---------------:|:--------:|:------:|
| 0.6914        | 1.7241  | 50   | 0.7021          | 0.4138   | 0.2422 |
| 0.6881        | 3.4483  | 100  | 0.6818          | 0.5862   | 0.5833 |
| 0.6284        | 5.1724  | 150  | 0.6509          | 0.6207   | 0.6234 |
| 0.5051        | 6.8966  | 200  | 0.9063          | 0.5517   | 0.4977 |
| 0.3431        | 8.6207  | 250  | 1.1387          | 0.5862   | 0.5882 |
| 0.2236        | 10.3448 | 300  | 1.3533          | 0.5517   | 0.5539 |
| 0.098         | 12.0690 | 350  | 1.8198          | 0.5517   | 0.5539 |
| 0.0527        | 13.7931 | 400  | 1.9629          | 0.5517   | 0.5539 |


### Framework versions

- Transformers 4.41.0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1