summarization_model – AI Model by madanagrawal | AlphaNeural AI

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madanagrawal/
summarization_model

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text2text-generation

generated_from_trainer

google-t5/t5-small

text-generation-inference

endpoints_compatible

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summarizsation_model

This model is a fine-tuned version of google-t5/t5-small on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 2.4501
Rouge1: 0.138
Rouge2: 0.0529
Rougel: 0.1162
Rougelsum: 0.1161
Gen Len: 19.0

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: 16
eval_batch_size: 16
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	Gen Len
No log	1.0	62	2.7359	0.123	0.0372	0.1042	0.104	19.0
No log	2.0	124	2.5299	0.1337	0.0498	0.1121	0.1122	19.0
No log	3.0	186	2.4669	0.1354	0.0509	0.1138	0.1139	19.0
No log	4.0	248	2.4501	0.138	0.0529	0.1162	0.1161	19.0

Framework versions

Transformers 4.40.1
Pytorch 2.2.1+cu121
Datasets 2.19.0
Tokenizers 0.19.1