---
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-10
  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-10

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: 0.7624
- Accuracy: 0.7675
- F1: 0.7491
- Precision: 0.7711
- Recall: 0.7457

## 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   | 123  | 1.5725          | 0.4236   | 0.2919 | 0.2961    | 0.339  |
| No log        | 2.0   | 246  | 1.1745          | 0.6051   | 0.4965 | 0.6084    | 0.5353 |
| No log        | 3.0   | 369  | 0.9715          | 0.7166   | 0.6859 | 0.7459    | 0.6734 |
| No log        | 4.0   | 492  | 0.7882          | 0.7834   | 0.7679 | 0.7870    | 0.7656 |
| 1.3067        | 5.0   | 615  | 0.7624          | 0.7675   | 0.7491 | 0.7711    | 0.7457 |


### Framework versions

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