---
library_name: transformers
license: mit
base_model: FacebookAI/xlm-roberta-large
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: xlm-roberta-large_product_classifier
  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_product_classifier

This model is a fine-tuned version of [FacebookAI/xlm-roberta-large](https://huggingface.co/FacebookAI/xlm-roberta-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3981
- Accuracy: 0.8169

## 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: 32
- eval_batch_size: 32
- 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: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 490  | 0.8869          | 0.7423   |
| 1.3297        | 2.0   | 980  | 0.7796          | 0.7798   |
| 0.7265        | 3.0   | 1470 | 0.7592          | 0.7872   |
| 0.5509        | 4.0   | 1960 | 0.8112          | 0.7949   |
| 0.4258        | 5.0   | 2450 | 0.8498          | 0.7875   |
| 0.3307        | 6.0   | 2940 | 0.8326          | 0.8036   |
| 0.2702        | 7.0   | 3430 | 0.8833          | 0.8066   |
| 0.2078        | 8.0   | 3920 | 0.9260          | 0.8066   |
| 0.1571        | 9.0   | 4410 | 0.9800          | 0.8087   |
| 0.1242        | 10.0  | 4900 | 1.0725          | 0.8043   |
| 0.0962        | 11.0  | 5390 | 1.2147          | 0.7946   |
| 0.0857        | 12.0  | 5880 | 1.1705          | 0.8123   |
| 0.0667        | 13.0  | 6370 | 1.2551          | 0.8041   |
| 0.052         | 14.0  | 6860 | 1.2762          | 0.8184   |
| 0.0414        | 15.0  | 7350 | 1.3442          | 0.8115   |
| 0.0313        | 16.0  | 7840 | 1.3510          | 0.8130   |
| 0.0247        | 17.0  | 8330 | 1.3754          | 0.8133   |
| 0.0158        | 18.0  | 8820 | 1.3915          | 0.8135   |
| 0.0162        | 19.0  | 9310 | 1.3975          | 0.8186   |
| 0.0109        | 20.0  | 9800 | 1.3981          | 0.8169   |


### Framework versions

- Transformers 4.48.0
- Pytorch 2.5.1+cu124
- Datasets 2.21.0
- Tokenizers 0.21.0