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distillbert-finetuned-codesearchnet

This model is a fine-tuned version of distilbert-base-uncased on the code_search_net dataset. It achieves the following results on the evaluation set:

  • Loss: 1.2471

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: 128
  • eval_batch_size: 128
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 3.0
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss
1.5595 1.0 7334 1.3620
1.3167 2.0 14668 1.2724
1.2549 3.0 22002 1.2471

Framework versions

  • Transformers 4.41.0
  • Pytorch 2.3.0+cu121
  • Datasets 2.19.1
  • Tokenizers 0.19.1
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Model size
67M params
Tensor type
F32
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Finetuned from

Dataset used to train gkteco/distillbert-finetuned-codesearchnet