---
library_name: transformers
license: mit
base_model: FacebookAI/xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: xlm-roberta-reddit-5
  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. -->

# xlm-roberta-reddit-5

This model is a fine-tuned version of [FacebookAI/xlm-roberta-base](https://huggingface.co/FacebookAI/xlm-roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4454
- Accuracy: 0.8677
- F1: 0.8380
- Precision: 0.8594
- Recall: 0.8353

## 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: 12
- eval_batch_size: 12
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| No log        | 1.0   | 74   | 1.0770          | 0.5185   | 0.3072 | 0.2694    | 0.3933 |
| No log        | 2.0   | 148  | 0.8862          | 0.6667   | 0.4737 | 0.4204    | 0.5580 |
| No log        | 3.0   | 222  | 0.6454          | 0.7143   | 0.5819 | 0.7749    | 0.6237 |
| No log        | 4.0   | 296  | 0.4804          | 0.8360   | 0.7701 | 0.8185    | 0.7899 |
| No log        | 5.0   | 370  | 0.4454          | 0.8677   | 0.8380 | 0.8594    | 0.8353 |


### Framework versions

- Transformers 4.48.3
- Pytorch 2.6.0+cu124
- Datasets 3.4.0
- Tokenizers 0.21.1