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
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Model tree for nahidcs/TokenizerTestingMTSUFall2024SoftwareEngineering
Base model
google-t5/t5-small