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bart-finetuned-samsum
adedamola26/bart-finetuned-samsum
bart-finetuned-samsum is a summarization model from adedamola26. Use it when you need a shorter version of a longer text. It is set up for transformers.
This model was trained by fine-tuning the facebook/bart-large-xsum model using these parameters and the samsum dataset.
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At a glance
- Task
- Summarization
- Library
- transformers
- Model type
- bart
- Access
- Public
- Created
- Mar 11, 2024
- Updated
- Mar 19, 2024
- SHA
- e7e3d08d
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Model card
From the Hugging Face model README
Description
This model was trained by fine-tuning the facebook/bart-large-xsum model using these parameters and the samsum dataset.
Development
- Jupyter Notebook: Text Summarization With BART
Usage
from transformers import pipeline
model = pipeline("summarization", model="adedamolade26/bart-finetuned-samsum")
conversation = '''Jack: Cocktails later?
May: YES!!!
May: You read my mind...
Jack: Possibly a little tightly strung today?
May: Sigh... without question.
Jack: Thought so.
May: A little drink will help!
Jack: Maybe two!
'''
model(conversation)
Training Parameters
evaluation_strategy = "epoch",
save_strategy = 'epoch',
load_best_model_at_end = True,
metric_for_best_model = 'eval_loss',
seed = 42,
learning_rate=2e-5,
per_device_train_batch_size=4,
per_device_eval_batch_size=4,
gradient_accumulation_steps=2,
weight_decay=0.01,
save_total_limit=2,
num_train_epochs=4,
predict_with_generate=True,
fp16=True,
report_to="none"
References
Model Training process was adapted from Luis Fernando Torres's Kaggle Notebook: 📝 Text Summarization with Large Language Models
- Task
- Summarization
- Library
- transformers
- Type
- bart
- Languages
- en
- Created
- Mar 11, 2024
- Updated
- Mar 19, 2024