---
license: mit
base_model: FacebookAI/xlm-roberta-base
tags:
- generated_from_trainer
model-index:
- name: e3_lr2e-05
  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. -->

# e3_lr2e-05

This model is a fine-tuned version of [FacebookAI/xlm-roberta-base](https://huggingface.co/FacebookAI/xlm-roberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6436

## 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: 16
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 2.9961        | 0.1404 | 100  | 1.9416          |
| 2.0472        | 0.2808 | 200  | 1.8589          |
| 1.9766        | 0.4212 | 300  | 1.8095          |
| 1.9319        | 0.5616 | 400  | 1.7736          |
| 1.897         | 0.7021 | 500  | 1.7447          |
| 1.8743        | 0.8425 | 600  | 1.7370          |
| 1.86          | 0.9829 | 700  | 1.7156          |
| 1.8431        | 1.1233 | 800  | 1.7071          |
| 1.8217        | 1.2637 | 900  | 1.6939          |
| 1.8212        | 1.4041 | 1000 | 1.6900          |
| 1.8053        | 1.5445 | 1100 | 1.6774          |
| 1.7899        | 1.6849 | 1200 | 1.6736          |
| 1.799         | 1.8254 | 1300 | 1.6644          |
| 1.7845        | 1.9658 | 1400 | 1.6559          |
| 1.7704        | 2.1062 | 1500 | 1.6531          |
| 1.776         | 2.2466 | 1600 | 1.6528          |
| 1.773         | 2.3870 | 1700 | 1.6417          |
| 1.7632        | 2.5274 | 1800 | 1.6452          |
| 1.7451        | 2.6678 | 1900 | 1.6460          |
| 1.7505        | 2.8088 | 2000 | 1.6455          |
| 1.7602        | 2.9492 | 2100 | 1.6399          |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1