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syssec-utd/py36-pylingual-v1-segmenter

sourceHugging Faceupdated 2y agoView on Hugging Face
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py36-pylingual-v1-segmenter

This model is a fine-tuned version of syssec-utd/py36-pylingual-v1-mlm on the syssec-utd/segmentation-py36-pylingual-v1-tokenized dataset. It achieves the following results on the evaluation set:

  • —Loss: 0.0006
  • —Precision: 1.0
  • —Recall: 1.0
  • —F1: 1.0
  • —Accuracy: 1.0

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
  • —trainbatchsize: 48
  • —evalbatchsize: 8
  • —seed: 42
  • —distributed_type: multi-GPU
  • —optimizer: Use OptimizerNames.ADAMWTORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizerargs=No additional optimizer arguments
  • —lrschedulertype: linear
  • —num_epochs: 2
  • —mixedprecisiontraining: Native AMP

Training results

Training LossEpochStepValidation LossPrecisionRecallF1Accuracy
0.00511.0908400.00141.01.01.01.0
0.00292.01816800.00061.01.01.01.0

Framework versions

  • —Transformers 4.48.2
  • —Pytorch 2.4.1+cu121
  • —Datasets 3.0.1
  • —Tokenizers 0.21.0