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

# base

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: 1.3065
- Accuracy: 0.8228
- F1: 0.7716
- Precision: 0.8261
- Recall: 0.7238

## 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 | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.6706        | 1.0   | 64   | 0.5822          | 0.6811   | 0.5424 | 0.6667    | 0.4571 |
| 0.5059        | 2.0   | 128  | 0.5081          | 0.7520   | 0.6595 | 0.7625    | 0.5810 |
| 0.2901        | 3.0   | 192  | 0.5731          | 0.8465   | 0.7958 | 0.8837    | 0.7238 |
| 0.2094        | 4.0   | 256  | 0.7700          | 0.8189   | 0.7629 | 0.8315    | 0.7048 |
| 0.1235        | 5.0   | 320  | 1.0102          | 0.8150   | 0.7459 | 0.8625    | 0.6571 |
| 0.0435        | 6.0   | 384  | 1.0899          | 0.8268   | 0.7755 | 0.8352    | 0.7238 |
| 0.0099        | 7.0   | 448  | 1.2422          | 0.8268   | 0.7582 | 0.8961    | 0.6571 |
| 0.0111        | 8.0   | 512  | 1.2646          | 0.8386   | 0.7760 | 0.9103    | 0.6762 |
| 0.0023        | 9.0   | 576  | 1.2875          | 0.8228   | 0.7783 | 0.8061    | 0.7524 |
| 0.003         | 10.0  | 640  | 1.3065          | 0.8228   | 0.7716 | 0.8261    | 0.7238 |


### Framework versions

- Transformers 4.43.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.19.1
- Tokenizers 0.19.1