t5_billsum_model – AI Model by geshijoker | AlphaNeural AI

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geshijoker/
t5_billsum_model

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text2text-generation

generated_from_trainer

google-t5/t5-small

text-generation-inference

endpoints_compatible

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t5_billsum_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: 2.6878
Rouge1: 0.1347
Rouge2: 0.0445
Rougel: 0.1138
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: 32
eval_batch_size: 32
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	31	3.1584	0.1359	0.0442	0.1156	0.1155	19.0
No log	2.0	62	2.8302	0.1315	0.0407	0.111	0.1112	19.0
No log	3.0	93	2.7160	0.133	0.0426	0.1129	0.1127	19.0
No log	4.0	124	2.6878	0.1347	0.0445	0.1138	0.1138	19.0

Framework versions

Transformers 4.45.0.dev0
Pytorch 2.2.1+cu118
Datasets 2.21.0
Tokenizers 0.19.1