---
license: apache-2.0
base_model: facebook/bart-large
tags:
- generated_from_trainer
model-index:
- name: multichoice-question-generator
  results: []
---



# multichoice-question-generator

This model is a fine-tuned version of [facebook/bart-large](https://huggingface.co/facebook/bart-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1787

## Model description

More information needed

## Intended uses & limitations
This is an early version of a model meant to generate multichoice questions from text
To load the model: 
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM

tokenizer = AutoTokenizer.from_pretrained("Gachomba/multichoice-question-generator")
model = AutoModelForSeq2SeqLM.from_pretrained("Gachomba/multichoice-question-generator")
# tokenize input text
import torch
device = "cuda" if torch.cuda.is_available() else "cpu"

def tokenize_input(input_text):
    inputs = tokenizer(input_text, return_tensors="pt", truncation=True, padding='max_length', max_length=1024)
    return inputs.input_ids.to(device), inputs.attention_mask.to(device)

# generate output from the model
def generate_output(input_text):
    input_ids, attention_mask = tokenize_input(input_text)
    outputs = model.generate(input_ids=input_ids, attention_mask=attention_mask, max_length=512)
    return tokenizer.decode(outputs[0], skip_special_tokens=True)

# get user input and generate a response
def get_response():
    user_input = input("Enter your text: ")
    response = generate_output(user_input)
    print("Generated Output:", response)

get_response()



## Training and evaluation data

More information needed

## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 0.2218        | 1.0   | 1000 | 0.1910          |
| 0.1913        | 2.0   | 2000 | 0.1811          |
| 0.1727        | 3.0   | 3000 | 0.1787          |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Tokenizers 0.19.1