PTS-Bart-Large-CNN – AI Model by ahmedmbutt | AlphaNeural AI

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ahmedmbutt/
PTS-Bart-Large-CNN

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text2text-generation

generated_from_trainer

ahmedmbutt/PTS-Dataset

facebook/bart-large-cnn

endpoints_compatible

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PTS-Bart-Large-CNN

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

Loss: 1.1760
Rouge1: 0.6551
Rouge2: 0.4332
Rougel: 0.5543
Rougelsum: 0.5541
Gen Len: 80.0886

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: 8
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
No log	1.0	220	0.8239	0.6263	0.3973	0.5238	0.5237	84.2023
No log	2.0	440	0.8201	0.6461	0.4184	0.5417	0.5416	81.1659
0.7121	3.0	660	0.8661	0.6479	0.4226	0.5448	0.5454	80.5409
0.7121	4.0	880	0.9784	0.6474	0.4242	0.5424	0.5425	82.2932
0.2619	5.0	1100	1.0645	0.655	0.4327	0.5517	0.5517	80.8386
0.2619	6.0	1320	1.1098	0.6548	0.4339	0.5542	0.5543	81.3545
0.1124	7.0	1540	1.1528	0.6528	0.4298	0.5511	0.551	80.5705
0.1124	8.0	1760	1.1760	0.6551	0.4332	0.5543	0.5541	80.0886

Framework versions

Transformers 4.41.2
Pytorch 2.3.0+cu121
Datasets 2.20.0
Tokenizers 0.19.1