Summary – AI Model by LogischeIP | AlphaNeural AI

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LogischeIP/
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text2text-generation

generated_from_trainer

google-t5/t5-small

text-generation-inference

endpoints_compatible

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Summary

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

Loss: 1.7430
Rouge1: 0.2448
Rouge2: 0.1173
Rougel: 0.2028
Rougelsum: 0.2029
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: 5
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
No log	1.0	282	1.7743	0.2429	0.1151	0.2007	0.2008	18.9976
2.0101	2.0	564	1.7550	0.2448	0.1169	0.203	0.2032	18.9976
2.0101	3.0	846	1.7477	0.2451	0.1178	0.2034	0.2036	18.9976
1.9145	4.0	1128	1.7441	0.2449	0.1173	0.2028	0.203	18.9976
1.9145	5.0	1410	1.7430	0.2448	0.1173	0.2028	0.2029	19.0

Framework versions

Transformers 4.35.2
Pytorch 2.1.0+cu121
Datasets 2.15.0
Tokenizers 0.15.0