---
library_name: transformers
license: mit
base_model: FacebookAI/xlm-roberta-large
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: xlm_roberta_lr2e-05_bs8_ep4
  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_lr2e-05_bs8_ep4

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: 0.1877
- Precision: 0.8767
- Recall: 0.8156
- F1: 0.8451
- Accuracy: 0.9243

## 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: 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: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.4701        | 1.0   | 430  | 0.3638          | 0.7295    | 0.5499 | 0.6271 | 0.8346   |
| 0.3818        | 2.0   | 860  | 0.3044          | 0.7008    | 0.8110 | 0.7519 | 0.8646   |
| 0.3108        | 3.0   | 1290 | 0.2210          | 0.8129    | 0.8267 | 0.8197 | 0.9080   |
| 0.2399        | 4.0   | 1720 | 0.1877          | 0.8767    | 0.8156 | 0.8451 | 0.9243   |


### Framework versions

- Transformers 4.47.0.dev0
- Pytorch 2.5.1+cu124
- Datasets 3.0.1
- Tokenizers 0.20.1