bart-base-finetuned-summarization-cnn-ver1.1 – AI Model by Alred | AlphaNeural AI

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Alred/
bart-base-finetuned-summarization-cnn-ver1.1

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bart-base-finetuned-summarization-cnn-ver1.1

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

Loss: 2.3824
Bertscore-mean-precision: 0.8904
Bertscore-mean-recall: 0.8610
Bertscore-mean-f1: 0.8753
Bertscore-median-precision: 0.8893
Bertscore-median-recall: 0.8606
Bertscore-median-f1: 0.8744

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: 5e-05
train_batch_size: 1
eval_batch_size: 1
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	Bertscore-mean-precision	Bertscore-mean-recall	Bertscore-mean-f1	Bertscore-median-precision	Bertscore-median-recall	Bertscore-median-f1
2.4217	1.0	5742	2.3095	0.8824	0.8582	0.8700	0.8822	0.8559	0.8696
1.7335	2.0	11484	2.2855	0.8907	0.8610	0.8754	0.8907	0.8600	0.8746
1.3013	3.0	17226	2.3824	0.8904	0.8610	0.8753	0.8893	0.8606	0.8744

Framework versions

Transformers 4.24.0
Pytorch 1.12.1+cu113
Datasets 2.7.1
Tokenizers 0.13.2