t5-small-codesearchnet-multilang-python

This model is a fine-tuned version of t5-small on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0682
  • Bleu: 0.0401
  • Rouge1: 0.6333
  • Rouge2: 0.6147
  • Avg Length: 16.9514

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: 5e-05
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 10
  • total_train_batch_size: 80
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 15

Training results

Training Loss Epoch Step Validation Loss Bleu Rouge1 Rouge2 Avg Length
No log 1.0 375 0.0717 0.0407 0.6244 0.6063 17.046
1.6287 2.0 750 0.0589 0.041 0.6321 0.6136 16.9924
0.0592 3.0 1125 0.0551 0.0402 0.6334 0.6152 16.971
0.0511 4.0 1500 0.0542 0.0402 0.6336 0.6155 16.9718
0.0511 5.0 1875 0.0529 0.0401 0.6343 0.6161 16.961
0.0441 6.0 2250 0.0531 0.0402 0.6341 0.6158 16.9626
0.0399 7.0 2625 0.0521 0.0402 0.6337 0.6154 16.97
0.0351 8.0 3000 0.0547 0.0401 0.6341 0.6159 16.964
0.0351 9.0 3375 0.0545 0.0402 0.635 0.6167 16.962
0.0301 10.0 3750 0.0557 0.0402 0.6342 0.6159 16.9646
0.027 11.0 4125 0.0569 0.0402 0.6342 0.6157 16.9622
0.0239 12.0 4500 0.0606 0.0401 0.6342 0.6158 16.9564
0.0239 13.0 4875 0.0616 0.0401 0.6343 0.6163 16.963
0.02 14.0 5250 0.0672 0.0401 0.6336 0.6154 16.9648
0.0185 15.0 5625 0.0682 0.0401 0.6333 0.6147 16.9514

Framework versions

  • Transformers 4.28.1
  • Pytorch 2.0.0+cu118
  • Datasets 2.12.0
  • Tokenizers 0.13.3
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