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

# lora_fine_tuned_copa_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: 0.6929
- Accuracy: 0.58
- F1: 0.58

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.6951        | 1.0   | 50   | 0.6928          | 0.56     | 0.5589 |
| 0.6949        | 2.0   | 100  | 0.6928          | 0.58     | 0.5790 |
| 0.6899        | 3.0   | 150  | 0.6928          | 0.59     | 0.5895 |
| 0.6906        | 4.0   | 200  | 0.6929          | 0.58     | 0.58   |
| 0.6953        | 5.0   | 250  | 0.6929          | 0.58     | 0.58   |
| 0.6949        | 6.0   | 300  | 0.6929          | 0.58     | 0.58   |
| 0.6985        | 7.0   | 350  | 0.6929          | 0.58     | 0.58   |
| 0.6912        | 8.0   | 400  | 0.6929          | 0.58     | 0.58   |


### Framework versions

- PEFT 0.11.1
- Transformers 4.41.0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1