---
library_name: transformers
license: mit
base_model: xlm-roberta-large
tags:
- generated_from_trainer
model-index:
- name: xlm-roberta-large
  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-large

This model is a fine-tuned version of [xlm-roberta-large](https://huggingface.co/xlm-roberta-large) on the None dataset.

## 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 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: 1

### Training results

| Training Loss | Epoch | Step | Validation Loss | Date                                                       | Loc                                                                                             | Org                                                                                                     | Per                                                        | Price                                                      | Product                                                                                                 | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:----------------------------------------------------------:|:-----------------------------------------------------------------------------------------------:|:-------------------------------------------------------------------------------------------------------:|:----------------------------------------------------------:|:----------------------------------------------------------:|:-------------------------------------------------------------------------------------------------------:|:-----------------:|:--------------:|:----------:|:----------------:|
| No log        | 1.0   | 100  | 0.0445          | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 39} | {'precision': 0.8984375, 'recall': 0.9274193548387096, 'f1': 0.9126984126984127, 'number': 124} | {'precision': 0.8448275862068966, 'recall': 0.8305084745762712, 'f1': 0.8376068376068375, 'number': 59} | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 70} | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 79} | {'precision': 0.9230769230769231, 'recall': 0.9230769230769231, 'f1': 0.9230769230769231, 'number': 13} | 0.9406            | 0.9479         | 0.9442     | 0.9859           |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0