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TokenizerTestingMTSUFall2024SoftwareEngineering – AI Model by nahidcs | AlphaNeural AI

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nahidcs/
TokenizerTestingMTSUFall2024SoftwareEngineering

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text2text-generation

generated_from_trainer

google-t5/t5-small

text-generation-inference

endpoints_compatible

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TokenizerTestingMTSUFall2024SoftwareEngineering

This model is a fine-tuned version of google-t5/t5-small on the None dataset.

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: 4
eval_batch_size: 4
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 4
mixed_precision_training: Native AMP

Framework versions

Transformers 4.45.2
Pytorch 1.13.0+cu117
Datasets 3.0.1
Tokenizers 0.20.1