billsum_model – AI Model by Chung-Fan | AlphaNeural AI

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Chung-Fan/
billsum_model

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text2text-generation

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text-generation-inference

endpoints_compatible

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my_awesome_billsum_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: 2.5147
Rouge1: 0.1392
Rouge2: 0.0483
Rougel: 0.1139
Rougelsum: 0.1138
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

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
No log	1.0	62	2.7989	0.1277	0.0376	0.1053	0.1052	19.0
No log	2.0	124	2.5915	0.1339	0.0453	0.1111	0.1108	19.0
No log	3.0	186	2.5304	0.1388	0.0488	0.1142	0.1141	19.0
No log	4.0	248	2.5147	0.1392	0.0483	0.1139	0.1138	19.0

Framework versions

Transformers 4.30.2
Pytorch 2.0.1+cu118
Datasets 2.13.1
Tokenizers 0.13.3