peft-starcoder-finetuned-cpp

This model is a fine-tuned version of bigcode/starcoderbase-1b on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.6176

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-06
  • train_batch_size: 2
  • eval_batch_size: 2
  • seed: 42
  • gradient_accumulation_steps: 8
  • total_train_batch_size: 16
  • optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_steps: 20
  • training_steps: 1000

Training results

Training Loss Epoch Step Validation Loss
0.9707 0.1273 20 0.9157
0.9027 0.2546 40 0.8960
0.7973 0.3819 60 0.8843
0.7716 0.5091 80 0.8618
0.6858 0.6364 100 0.8392
0.6603 0.7637 120 0.8126
0.6288 0.8910 140 0.7950
0.5693 1.0183 160 0.7798
0.5035 1.1456 180 0.7706
0.5376 1.2729 200 0.7583
0.4893 1.4002 220 0.7469
0.5256 1.5274 240 0.7366
0.4646 1.6547 260 0.7262
0.5039 1.7820 280 0.7156
0.4376 1.9093 300 0.7062
0.4262 2.0366 320 0.7000
0.445 2.1639 340 0.6917
0.4307 2.2912 360 0.6847
0.4531 2.4185 380 0.6822
0.4018 2.5457 400 0.6758
0.4466 2.6730 420 0.6695
0.3934 2.8003 440 0.6649
0.3815 2.9276 460 0.6607
0.3834 3.0549 480 0.6575
0.4001 3.1822 500 0.6523
0.398 3.3095 520 0.6481
0.3824 3.4368 540 0.6453
0.3756 3.5640 560 0.6409
0.3843 3.6913 580 0.6382
0.3829 3.8186 600 0.6357
0.3534 3.9459 620 0.6345
0.4136 4.0732 640 0.6343
0.3409 4.2005 660 0.6321
0.357 4.3278 680 0.6288
0.397 4.4551 700 0.6263
0.3713 4.5823 720 0.6255
0.3914 4.7096 740 0.6242
0.3657 4.8369 760 0.6230
0.3711 4.9642 780 0.6216
0.3538 5.0915 800 0.6205
0.377 5.2188 820 0.6199
0.3426 5.3461 840 0.6194
0.3583 5.4733 860 0.6188
0.3643 5.6006 880 0.6180
0.362 5.7279 900 0.6178
0.388 5.8552 920 0.6177
0.3424 5.9825 940 0.6177
0.3614 6.1098 960 0.6176
0.3652 6.2371 980 0.6176
0.3691 6.3644 1000 0.6176

Framework versions

  • PEFT 0.13.2
  • Transformers 4.46.2
  • Pytorch 2.4.1+cu121
  • Datasets 3.0.1
  • Tokenizers 0.20.3
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