---
library_name: transformers
language:
- en
base_model: cardiffnlp/twitter-roberta-base-sentiment
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: twitter-roberta-base-sentiment-finetuned-sentiment
  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-roberta-base-sentiment-finetuned-sentiment

This model is a fine-tuned version of [cardiffnlp/twitter-roberta-base-sentiment](https://huggingface.co/cardiffnlp/twitter-roberta-base-sentiment) on the Twitter Sentiment Datasets dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4905
- Accuracy: 0.8123

## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.5275        | 1.0   | 1250 | 0.4646          | 0.8098   |
| 0.4013        | 2.0   | 2500 | 0.4905          | 0.8123   |
| 0.2941        | 3.0   | 3750 | 0.5455          | 0.8104   |
| 0.2136        | 4.0   | 5000 | 0.6100          | 0.8096   |


### Framework versions

- Transformers 4.46.3
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3