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---
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
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