bart-large-cnn-finetuned-qmsum-2-4 – AI Model by Mohammad-basheer | AlphaNeural AI

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Mohammad-basheer/
bart-large-cnn-finetuned-qmsum-2-4

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text2text-generation

qmsum-summarization

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bart-large-cnn-finetuned-qmsum-2-4

This model is a fine-tuned version of facebook/bart-large-cnn on the None dataset. It achieves the following results on the evaluation set:

Loss: 4.0277
Rouge1: 0.3053
Rouge2: 0.0660
Rougel: 0.1903
Rougelsum: 0.2598

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 5.6e-05
train_batch_size: 2
eval_batch_size: 2
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 4

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum
3.3773	1.0	629	3.2522	0.2964	0.0713	0.1958	0.2593
2.3656	2.0	1258	3.2001	0.2942	0.0694	0.1921	0.2540
1.5843	3.0	1887	3.4248	0.3086	0.0687	0.1938	0.2648
0.9854	4.0	2516	4.0277	0.3053	0.0660	0.1903	0.2598

Framework versions

Transformers 4.21.3
Pytorch 1.12.1+cu113
Datasets 2.4.0
Tokenizers 0.12.1