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trump_stance_detection
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---
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
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# 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