text-summarization-evaluation-model – AI Model by akash2212 | AlphaNeural AI

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akash2212/
text-summarization-evaluation-model

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text2text-generation

generated_from_trainer

google-t5/t5-small

text-generation-inference

endpoints_compatible

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text-summarization-evaluation-model

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

Loss: 2.4100
Rouge1: 0.1909
Rouge2: 0.0934
Rougel: 0.1617
Rougelsum: 0.1619
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	2.4775	0.1556	0.0622	0.1297	0.1301	19.0
No log	2.0	124	2.4374	0.1822	0.0868	0.1534	0.1537	19.0
No log	3.0	186	2.4164	0.1888	0.0922	0.16	0.1602	19.0
No log	4.0	248	2.4100	0.1909	0.0934	0.1617	0.1619	19.0

Framework versions

Transformers 4.35.2
Pytorch 2.1.0+cu121
Datasets 2.15.0
Tokenizers 0.15.0