---
license: apache-2.0
base_model: google/flan-t5-base
tags:
- generated_from_trainer
model-index:
- name: Fake-news-gen
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Fake-news-gen

This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on the None dataset.

Here is one way to write a professional model card description for your fake news generator model on Hugging Face:

# Summary

This model is a conditional text generation system fine-tuned to produce artificially generated news articles from short text summaries. It demonstrates the potential for AI systems to automatically synthesize false or misleading news content from limited input information.  

# Intended Uses

- Research on AI fake news generation capabilities and risks
- Educational purposes to increase awareness of AI fake content issues
- Testing automatic fake news detection systems 

# Factors

- Initially trained on summarization data (XSUM BBC news)
- Fine-tuned end-to-end to generate full articles from summaries  
- Generates content token-by-token based on summary prompt
- No ground-truth real/fake labels or classifier included
- Outputs are raw model decodes without post-processing  

# Caveats and Recommendations

- Output quality can vary, may require multiple sampling or overrides
- Content reflects training data biases and model limitations
- Not intended for malicious uses or dissemination
- Users should manually review outputs before reliance 


## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results



### Framework versions

- Transformers 4.36.0
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0