---
license: mit
base_model: xlm-roberta-base
tags:
- generated_from_trainer
model-index:
- name: xlm-roberta-base-finetuned-Adapter-ar-mlm-0.15-large-29OCT
  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-finetuned-Adapter-ar-mlm-0.15-large-29OCT

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: 2.0107
- Model Preparation Time: 0.0044

## 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: 0.0001
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 32
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 5

### Training results

| Training Loss | Epoch  | Step  | Validation Loss | Model Preparation Time |
|:-------------:|:------:|:-----:|:---------------:|:----------------------:|
| 3.5857        | 0.4703 | 1000  | 2.9678          | 0.0044                 |
| 2.8254        | 0.9407 | 2000  | 2.5072          | 0.0044                 |
| 2.5882        | 1.4110 | 3000  | 2.3254          | 0.0044                 |
| 2.4612        | 1.8814 | 4000  | 2.2290          | 0.0044                 |
| 2.3731        | 2.3517 | 5000  | 2.1540          | 0.0044                 |
| 2.316         | 2.8221 | 6000  | 2.1089          | 0.0044                 |
| 2.2806        | 3.2924 | 7000  | 2.0712          | 0.0044                 |
| 2.2416        | 3.7628 | 8000  | 2.0418          | 0.0044                 |
| 2.21          | 4.2331 | 9000  | 2.0209          | 0.0044                 |
| 2.1977        | 4.7035 | 10000 | 2.0107          | 0.0044                 |


### Framework versions

- Transformers 4.43.4
- Pytorch 2.1.1+cu121
- Datasets 3.0.2
- Tokenizers 0.19.1