---
license: mit
base_model: xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: xnli_en_adalora_alpha_32_drop_02_rank_16
  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. -->

# xnli_en_adalora_alpha_32_drop_02_rank_16

This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4329
- Accuracy: 0.8317

## 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: 0.0003
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10.0

### Training results

| Training Loss | Epoch | Step   | Validation Loss | Accuracy |
|:-------------:|:-----:|:------:|:---------------:|:--------:|
| 0.5524        | 1.0   | 12272  | 0.5105          | 0.7980   |
| 0.5069        | 2.0   | 24544  | 0.4791          | 0.8153   |
| 0.484         | 3.0   | 36816  | 0.5075          | 0.8000   |
| 0.4782        | 4.0   | 49088  | 0.4453          | 0.8249   |
| 0.4577        | 5.0   | 61360  | 0.4433          | 0.8305   |
| 0.448         | 6.0   | 73632  | 0.4361          | 0.8277   |
| 0.4223        | 7.0   | 85904  | 0.4379          | 0.8261   |
| 0.428         | 8.0   | 98176  | 0.4338          | 0.8361   |
| 0.4224        | 9.0   | 110448 | 0.4337          | 0.8353   |
| 0.4105        | 10.0  | 122720 | 0.4329          | 0.8317   |


### Framework versions

- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.18.0
- Tokenizers 0.19.1