---
tags:
- generated_from_trainer
base_model: cardiffnlp/twitter-roberta-base-sentiment-latest
metrics:
- accuracy
model-index:
- name: fine-tuned-twitter-roberta-base-sentiment-latest
  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. -->

# fine-tuned-twitter-roberta-base-sentiment-latest

This model is a fine-tuned version of [cardiffnlp/twitter-roberta-base-sentiment-latest](https://huggingface.co/cardiffnlp/twitter-roberta-base-sentiment-latest) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3062
- Accuracy: {'accuracy': 0.8868131868131868}
- F1score: {'f1': 0.88247351021472}

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy                         | F1score                    |
|:-------------:|:------:|:----:|:---------------:|:--------------------------------:|:--------------------------:|
| 0.461         | 0.2443 | 500  | 0.3381          | {'accuracy': 0.8565934065934065} | {'f1': 0.8483856477235431} |
| 0.3702        | 0.4885 | 1000 | 0.3378          | {'accuracy': 0.865934065934066}  | {'f1': 0.8655309886906097} |
| 0.3574        | 0.7328 | 1500 | 0.2971          | {'accuracy': 0.8714285714285714} | {'f1': 0.8709435986031107} |
| 0.3358        | 0.9770 | 2000 | 0.3062          | {'accuracy': 0.8868131868131868} | {'f1': 0.88247351021472}   |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1