SolCoder

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

  • Loss: 0.5568

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: 0.0001
  • train_batch_size: 37
  • eval_batch_size: 37
  • seed: 100
  • distributed_type: multi-GPU
  • num_devices: 4
  • total_train_batch_size: 148
  • total_eval_batch_size: 148
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 20

Training results

Training Loss Epoch Step Validation Loss
0.6094 1.0 7440 0.6185
0.598 2.0 14880 0.6124
0.5845 3.0 22320 0.6075
0.5723 4.0 29760 0.6006
0.5589 5.0 37200 0.5943
0.5495 6.0 44640 0.5894
0.5371 7.0 52080 0.5861
0.5291 8.0 59520 0.5811
0.52 9.0 66960 0.5765
0.5095 10.0 74400 0.5746
0.5056 11.0 81840 0.5700
0.4967 12.0 89280 0.5682
0.4894 13.0 96720 0.5659
0.4861 14.0 104160 0.5619
0.4773 15.0 111600 0.5599
0.4754 16.0 119040 0.5599
0.4689 17.0 126480 0.5578
0.4642 18.0 133920 0.5575
0.4627 19.0 141360 0.5566
0.4573 20.0 148800 0.5568

Framework versions

  • Transformers 4.33.0
  • Pytorch 2.1.0+cu121
  • Datasets 2.11.0
  • Tokenizers 0.13.3
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