led-base-16384-biolaysum-both-scite – AI Model by domenicrosati | AlphaNeural AI

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led-base-16384-biolaysum-both-scite

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led-base-16384-biolaysum-both-scite

This model is a fine-tuned version of allenai/led-base-16384 on the None dataset. It achieves the following results on the evaluation set:

Loss: 2.1342
Rouge1: 0.4546
Rouge2: 0.1577
Rougel: 0.2458
Rougelsum: 0.2459

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: 4
eval_batch_size: 4
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 4
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum
2.2504	0.69	5000	2.1945	0.4499	0.1547	0.2439	0.2439
2.0172	1.37	10000	2.1342	0.4546	0.1577	0.2458	0.2459
1.9011	2.06	15000	2.1019	0.4542	0.1558	0.2435	0.2435
1.8777	2.75	20000	2.0869	0.4565	0.1567	0.2433	0.2434
1.7547	3.43	25000	2.0740	0.4556	0.1563	0.2444	0.2444

Framework versions

Transformers 4.26.0
Pytorch 1.13.1
Datasets 2.10.1
Tokenizers 0.12.1