---
license: mit
base_model: FacebookAI/xlm-roberta-large
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: finetuned_xlmroberta_model
  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. -->

# finetuned_xlmroberta_model

This model is a fine-tuned version of [FacebookAI/xlm-roberta-large](https://huggingface.co/FacebookAI/xlm-roberta-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0625
- Precision: 0.6892
- Recall: 0.7146
- F1: 0.7017
- Accuracy: 0.9750

## 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: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.0679        | 1.0   | 2185 | 0.0632          | 0.6915    | 0.7146 | 0.7029 | 0.9740   |
| 0.0555        | 2.0   | 4370 | 0.0625          | 0.6892    | 0.7146 | 0.7017 | 0.9750   |
| 0.0427        | 3.0   | 6555 | 0.0672          | 0.7040    | 0.7300 | 0.7167 | 0.9750   |
| 0.0318        | 4.0   | 8740 | 0.0810          | 0.7097    | 0.7660 | 0.7368 | 0.9743   |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1