---
license: mit
base_model: DeepaPeri/xlm-roberta-base-en-5
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: xlm-roberta-base-en-15
  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-en-15

This model is a fine-tuned version of [DeepaPeri/xlm-roberta-base-en-5](https://huggingface.co/DeepaPeri/xlm-roberta-base-en-5) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5872
- F1: 0.8359

## 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: 5e-05
- train_batch_size: 20
- eval_batch_size: 20
- 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 | F1     |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 0.1525        | 1.0   | 1000  | 0.3252          | 0.8107 |
| 0.1294        | 2.0   | 2000  | 0.3068          | 0.8076 |
| 0.1024        | 3.0   | 3000  | 0.3503          | 0.8117 |
| 0.0778        | 4.0   | 4000  | 0.3877          | 0.8248 |
| 0.0587        | 5.0   | 5000  | 0.4293          | 0.8113 |
| 0.0397        | 6.0   | 6000  | 0.4690          | 0.8235 |
| 0.0313        | 7.0   | 7000  | 0.4946          | 0.8283 |
| 0.0188        | 8.0   | 8000  | 0.5559          | 0.8327 |
| 0.0121        | 9.0   | 9000  | 0.5771          | 0.8361 |
| 0.0079        | 10.0  | 10000 | 0.5872          | 0.8359 |


### Framework versions

- Transformers 4.40.1
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1