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py315-pylingual-v3-statement – AI Model by syssec-utd | AlphaNeural AI

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syssec-utd/
py315-pylingual-v3-statement

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text2text-generation

generated_from_trainer

Salesforce/codet5-base

text-generation-inference

endpoints_compatible

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py315-pylingual-v3-statement

This model is a fine-tuned version of Salesforce/codet5-base on the syssec-utd/statement-py315-pylingual-v3-tokenized 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: 64
eval_batch_size: 64
seed: 42
distributed_type: multi-GPU
num_devices: 2
total_train_batch_size: 128
total_eval_batch_size: 128
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 2
mixed_precision_training: Native AMP

Training results

Framework versions

Transformers 5.12.1
Pytorch 2.12.0+cu130
Datasets 5.0.0
Tokenizers 0.22.2