---
base_model: cardiffnlp/twitter-xlm-roberta-base-sentiment
tags:
- generated_from_trainer
model-index:
- name: XlM-roberta-AS-HU-f1-score
  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-AS-HU-f1-score

This model is a fine-tuned version of [cardiffnlp/twitter-xlm-roberta-base-sentiment](https://huggingface.co/cardiffnlp/twitter-xlm-roberta-base-sentiment) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1081
- F1-score: 0.8389

## 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: 16
- 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

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1-score |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6852        | 1.0   | 64   | 0.6780          | 0.3697   |
| 0.6514        | 2.0   | 128  | 0.5578          | 0.6958   |
| 0.5075        | 3.0   | 192  | 0.5620          | 0.7619   |
| 0.401         | 4.0   | 256  | 0.5068          | 0.7688   |
| 0.2288        | 5.0   | 320  | 0.6490          | 0.8084   |
| 0.1424        | 6.0   | 384  | 0.7662          | 0.8350   |
| 0.0837        | 7.0   | 448  | 0.9138          | 0.8389   |
| 0.0463        | 8.0   | 512  | 1.0355          | 0.8247   |
| 0.0108        | 9.0   | 576  | 1.0874          | 0.8345   |
| 0.0069        | 10.0  | 640  | 1.1081          | 0.8389   |


### Framework versions

- Transformers 4.41.1
- Pytorch 2.0.1+cu117
- Datasets 2.19.1
- Tokenizers 0.19.1