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t5-neutralization – AI Model by agata-luk | AlphaNeural AI
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agata-luk
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t5-neutralization
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transformers
safetensors
t5
text2text-generation
simplification
generated_from_trainer
google-t5/t5-base
finetune
apache-2.0
text-generation-inference
endpoints_compatible
us
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t5-neutralization
This model is a fine-tuned version of
google-t5/t5-base
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.0245
Bleu: 54.8996
Gen Len: 18.7604
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: 2
Training results
Training Loss
Epoch
Step
Validation Loss
Bleu
Gen Len
No log
1.0
440
0.0303
54.7693
18.6667
0.06
2.0
880
0.0245
54.8996
18.7604
Framework versions
Transformers 4.51.2
Pytorch 2.10.0+cu128
Datasets 4.0.0
Tokenizers 0.21.4
