---
base_model: cardiffnlp/twitter-xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- f1
- recall
- accuracy
model-index:
- name: twitter-xlm-roberta-finetuned-class
  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. -->

# twitter-xlm-roberta-finetuned-class

This model is a fine-tuned version of [cardiffnlp/twitter-xlm-roberta-base](https://huggingface.co/cardiffnlp/twitter-xlm-roberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7774
- F1: 0.7098
- Recall: 0.7333
- Accuracy: 0.7195

## 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: 1.7197827530913808e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 101
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     | Recall | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:--------:|
| 0.9152        | 1.44  | 500  | 0.7553          | 0.7047 | 0.7156 | 0.7195   |
| 0.5205        | 2.87  | 1000 | 0.7774          | 0.7098 | 0.7333 | 0.7195   |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0