t5-neutralisation – AI Model by carmengoar | AlphaNeural AI

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carmengoar/
t5-neutralisation

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text2text-generation

generated_from_trainer

google-t5/t5-small

text-generation-inference

endpoints_compatible

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t5-neutralisation

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

Loss: 0.0593
Bleu: 54.7416
Gen Len: 18.7292

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: 5.6e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 6

Training results

Training Loss	Epoch	Step	Validation Loss	Bleu	Gen Len
No log	1.0	440	0.0837	53.9225	18.6042
0.0369	2.0	880	0.0739	54.1449	18.6354
0.034	3.0	1320	0.0690	54.4631	18.6562
0.0346	4.0	1760	0.0625	54.7416	18.7292
0.0423	5.0	2200	0.0599	54.7416	18.7292
0.0406	6.0	2640	0.0593	54.7416	18.7292

Framework versions

Transformers 4.51.2
Pytorch 2.10.0+cu128
Datasets 4.0.0
Tokenizers 0.21.4