---
library_name: transformers
base_model: cardiffnlp/twitter-xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: binary_classification2
  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. -->

# binary_classification2

This model is a fine-tuned version of [cardiffnlp/twitter-xlm-roberta-base](https://huggingface.co/cardiffnlp/twitter-xlm-roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7178
- F1: 0.7750

## 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: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch  | Step | Validation Loss | F1     |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 0.4132        | 0.2625 | 100  | 0.4500          | 0.7621 |
| 0.6075        | 0.5249 | 200  | 0.4293          | 0.7781 |
| 0.3672        | 0.7874 | 300  | 0.3937          | 0.7964 |
| 0.3682        | 1.0499 | 400  | 0.4572          | 0.7864 |
| 0.3747        | 1.3123 | 500  | 0.4268          | 0.7946 |
| 0.339         | 1.5748 | 600  | 0.4087          | 0.7853 |
| 0.4468        | 1.8373 | 700  | 0.4649          | 0.7972 |
| 0.2621        | 2.0997 | 800  | 0.4521          | 0.7889 |
| 0.2443        | 2.3622 | 900  | 0.5213          | 0.7927 |
| 0.289         | 2.6247 | 1000 | 0.5290          | 0.7749 |
| 0.3365        | 2.8871 | 1100 | 0.4803          | 0.7835 |
| 0.3744        | 3.1496 | 1200 | 0.6371          | 0.7861 |
| 0.2841        | 3.4121 | 1300 | 0.6773          | 0.7881 |
| 0.2847        | 3.6745 | 1400 | 0.6217          | 0.7826 |
| 0.1881        | 3.9370 | 1500 | 0.6898          | 0.7807 |
| 0.0901        | 4.1995 | 1600 | 0.7506          | 0.7726 |
| 0.1814        | 4.4619 | 1700 | 0.7278          | 0.7760 |
| 0.3393        | 4.7244 | 1800 | 0.7157          | 0.7729 |
| 0.2436        | 4.9869 | 1900 | 0.7178          | 0.7750 |


### Framework versions

- Transformers 4.45.1
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.20.0