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codet5-small-v2

This model is a fine-tuned version of Salesforce/codet5-small on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0818
  • Rouge1: 90.2445
  • Rouge2: 87.8925
  • Rougel: 90.3346
  • Rougelsum: 90.4247
  • Gen Len: 13.7838

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: 16
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 10
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum Gen Len
No log 1.0 20 1.6233 60.4701 43.4599 57.215 56.9531 13.5135
No log 2.0 40 0.5503 79.3375 69.4176 75.4377 75.2854 13.5676
No log 3.0 60 0.2397 66.4876 55.0069 62.0571 61.9916 11.8378
No log 4.0 80 0.1486 78.7452 74.9876 78.6615 78.6958 14.4054
No log 5.0 100 0.1200 81.8039 78.3534 82.0292 82.0142 14.3243
No log 6.0 120 0.1040 81.8039 78.3534 82.0292 82.0142 14.3243
No log 7.0 140 0.0931 88.2604 84.8265 88.0824 88.3097 14.4324
No log 8.0 160 0.0857 88.2604 84.8265 88.0824 88.3097 14.4324
No log 9.0 180 0.0834 90.2445 87.8925 90.3346 90.4247 13.7838
No log 10.0 200 0.0818 90.2445 87.8925 90.3346 90.4247 13.7838

Framework versions

  • Transformers 4.38.0.dev0
  • Pytorch 2.1.0+cu121
  • Datasets 2.16.1
  • Tokenizers 0.15.1
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