py315-pylingual-v3-segmenter

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py315-pylingual-v3-segmenter

This model is a fine-tuned version of syssec-utd/py315-pylingual-v3-mlm on the syssec-utd/segmentation-py315-pylingual-v3-tokenized dataset. It achieves the following results on the evaluation set:

• Loss: 0.0078
• Precision: 0.9950
• Recall: 0.9947
• F1: 0.9948
• Accuracy: 0.9985

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: 8
• seed: 42
• distributed_type: multi-GPU
• num_devices: 2
• total_train_batch_size: 128
• total_eval_batch_size: 16
• 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