summarization – AI Model by phi0108 | AlphaNeural AI

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summarization

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text2text-generation

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text-generation-inference

endpoints_compatible

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summarization

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

Loss: 2.4987
Rouge1: 0.1453
Rouge2: 0.0544
Rougel: 0.1203
Rougelsum: 0.1202
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	2.7907	0.1226	0.0355	0.1036	0.1034	19.0
No log	2.0	124	2.5804	0.1343	0.0468	0.1126	0.1125	19.0
No log	3.0	186	2.5159	0.1441	0.0549	0.1198	0.1197	19.0
No log	4.0	248	2.4987	0.1453	0.0544	0.1203	0.1202	19.0

Framework versions

Transformers 4.27.4
Pytorch 2.0.0+cu118
Datasets 2.11.0
Tokenizers 0.13.3