Longformer-Encoder-Decoder-LED – AI Model by Zohaib002 | AlphaNeural AI | AlphaNeural AI

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Zohaib002/
Longformer-Encoder-Decoder-LED

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text2text-generation

generated_from_trainer

pszemraj/led-base-book-summary

endpoints_compatible

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

Loss: 1.0247
Rouge1: 0.6269
Rouge2: 0.3921
Rougel: 0.5261
Rougelsum: 0.5266
Gen Len: 67.5584

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: 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	274	1.0933	0.5918	0.3356	0.4785	0.4788	72.0547
1.1731	2.0	548	1.0177	0.5985	0.3525	0.4902	0.4906	68.5055
1.1731	3.0	822	0.9976	0.6063	0.3603	0.4982	0.4982	69.7263
0.7216	4.0	1096	0.9922	0.6113	0.3735	0.5081	0.5084	68.1861
0.7216	5.0	1370	0.9957	0.6193	0.3826	0.5216	0.5217	65.4617
0.5252	6.0	1644	1.0127	0.6252	0.3877	0.5231	0.5236	68.0584
0.5252	7.0	1918	1.0221	0.6252	0.3897	0.5246	0.5246	67.5931
0.4079	8.0	2192	1.0247	0.6269	0.3921	0.5261	0.5266	67.5584

Framework versions

Transformers 4.42.4
Pytorch 2.3.1+cu121
Datasets 2.20.0
Tokenizers 0.19.1