---
library_name: peft
tags:
- generated_from_trainer
base_model: cardiffnlp/twitter-roberta-base-sentiment-latest
metrics:
- accuracy
model-index:
- name: twitter-roberta-base-sentiment-latest-trump-stance
  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-latest-trump-stance

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: 0.3134
- Accuracy: {'accuracy': 0.87875}

## 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: 0.001
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy              |
|:-------------:|:-----:|:----:|:---------------:|:---------------------:|
| 0.5486        | 1.0   | 1800 | 0.5270          | {'accuracy': 0.79375} |
| 0.4626        | 2.0   | 3600 | 0.4231          | {'accuracy': 0.85375} |
| 0.4216        | 3.0   | 5400 | 0.3134          | {'accuracy': 0.87875} |


### Framework versions

- PEFT 0.10.0
- Transformers 4.38.2
- Pytorch 2.2.1
- Datasets 2.18.0
- Tokenizers 0.15.2