generated_from_trainer base_model:xlm-roberta-base license:mit region:us
---
license: mit
base_model: xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: xlm-roberta-base-lora-text-classification
  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-base-lora-text-classification

This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5536
- Accuracy: {'accuracy': 0.8980555555555556}

## 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: 0.001
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy                         |
|:-------------:|:-----:|:-----:|:---------------:|:--------------------------------:|
| 0.4165        | 1.0   | 3600  | 0.4468          | {'accuracy': 0.895}              |
| 0.5475        | 2.0   | 7200  | 0.4904          | {'accuracy': 0.8897222222222222} |
| 0.5878        | 3.0   | 10800 | 0.4564          | {'accuracy': 0.8986111111111111} |
| 0.6508        | 4.0   | 14400 | 0.4560          | {'accuracy': 0.8916666666666667} |
| 0.5914        | 5.0   | 18000 | 0.5437          | {'accuracy': 0.8883333333333333} |
| 0.5927        | 6.0   | 21600 | 0.5986          | {'accuracy': 0.8841666666666667} |
| 0.6044        | 7.0   | 25200 | 0.6523          | {'accuracy': 0.8791666666666667} |
| 0.6249        | 8.0   | 28800 | 0.6199          | {'accuracy': 0.8833333333333333} |
| 0.5427        | 9.0   | 32400 | 0.5363          | {'accuracy': 0.8969444444444444} |
| 0.5724        | 10.0  | 36000 | 0.5536          | {'accuracy': 0.8980555555555556} |


### Framework versions

- Transformers 4.33.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
