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---
license: mit
base_model: roberta-base
datasets: climate_fever
tags:
 - fact-checking
 - climate
 - text entailment
metrics:
- accuracy
- f1
model-index:
- name: results
  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. -->

# results

This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on Jasontth/climate_fever_plus, enlarged CLIMATE-FEVER dataset (The dataset provided combines the Climate-Fever dataset and claim reviews from the website Climate Feedback (https://climatefeedback.org/))
It achieves the following results on the evaluation set:
- Loss: 0.6970
- Accuracy: 0.7288
- F1: 0.7229


### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 16
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 10
- mixed_precision_training: Native AMP

### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0