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 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