question-generator

This model is a fine-tuned version of facebook/bart-large on the SQUAD dataset. It achieves the following results on the evaluation set:

• Loss: 3.1315

Model description

More information needed

Intended uses & limitations

Sample Usage

def generate_question(context): inputs = tokenizer(context, return_tensors="pt") output = model.generate(**inputs) question = tokenizer.decode(output[0], skip_special_tokens=True) return question print(generate_question("Paris is the capital city of France"))

Training and evaluation data

This model is trained and evaluated on the SQUAD dataset

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 2e-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: 3

Training results

Training Loss	Epoch	Step	Validation Loss
2.9322	1.0	10950	3.1334
2.6046	2.0	21900	3.1102
2.3742	3.0	32850	3.1315

Framework versions

• Transformers 4.42.3
• Pytorch 2.3.0+cu121
• Datasets 2.20.0
• Tokenizers 0.19.1