t5-small-ruleviewer – AI Model by Tgratzi | AlphaNeural AI

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Tgratzi/
t5-small-ruleviewer

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text2text-generation

generated_from_trainer

google-t5/t5-small

text-generation-inference

endpoints_compatible

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t5-small-ruleviewer

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

Loss: 0.0000

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: 0.001
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
lr_scheduler_warmup_steps: 200
num_epochs: 40

Training results

Training Loss	Epoch	Step	Validation Loss
0.8028	4.88	200	0.0162
0.0196	9.76	400	0.0010
0.0071	14.63	600	0.0002
0.0033	19.51	800	0.0001
0.0019	24.39	1000	0.0000
0.0014	29.27	1200	0.0000
0.0011	34.15	1400	0.0000
0.0008	39.02	1600	0.0000

Framework versions

Transformers 4.37.2
Pytorch 2.1.0+cu121
Datasets 2.17.1
Tokenizers 0.15.2