T5-PEFT-3 – AI Model by jgibb | AlphaNeural AI

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jgibb/
T5-PEFT-3

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google-t5/t5-base

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T5-PEFT-3

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

Loss: 1.1705

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: 0.0002
train_batch_size: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 2
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss
No log	0.18	250	1.3105
1.7303	0.35	500	1.2574
1.7303	0.53	750	1.2259
1.3176	0.71	1000	1.2101
1.3176	0.89	1250	1.2009
1.2971	1.06	1500	1.1895
1.2971	1.24	1750	1.1828
1.2582	1.42	2000	1.1804
1.2582	1.6	2250	1.1763
1.2579	1.77	2500	1.1730
1.2579	1.95	2750	1.1705

Framework versions

PEFT 0.10.0
Transformers 4.38.2
Pytorch 2.2.1+cu121
Datasets 2.18.0
Tokenizers 0.15.2