---
base_model: cardiffnlp/twitter-roberta-base-sentiment-latest
library_name: transformers
metrics:
- accuracy
tags:
- generated_from_trainer
model-index:
- name: twitter-roberta-sentiment-analysiss-lr-1e-5
  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-sentiment-analysiss-lr-1e-5

This model is a fine-tuned version of [cardiffnlp/twitter-roberta-base-sentiment-latest](https://huggingface.co/cardiffnlp/twitter-roberta-base-sentiment-latest) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5804
- Balanced Accuracy: 0.6492
- Accuracy: 0.6649

## 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: 1e-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
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Balanced Accuracy | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:-----------------:|:--------:|
| 0.4577        | 1.3889 | 200  | 0.4800          | 0.6217            | 0.5382   |
| 0.3676        | 2.7778 | 400  | 0.4861          | 0.6472            | 0.6059   |
| 0.3078        | 4.1667 | 600  | 0.5804          | 0.6492            | 0.6649   |


### Framework versions

- Transformers 4.46.2
- Pytorch 2.5.0+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3