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CodeExplainer-7b-v0.11-GPTQ

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metadata
license: apache-2.0
library_name: peft
tags:
  - generated_from_trainer
base_model: TheBloke/Marcoroni-7B-v3-GPTQ
model-index:
  - name: 20231215-144935
    results: []

20231215-144935

This model is a fine-tuned version of TheBloke/Marcoroni-7B-v3-GPTQ on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2792

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: 2.5e-05
  • train_batch_size: 2
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 2
  • training_steps: 100
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss
2.1951 0.02 1 2.0427
1.4965 0.03 2 2.0427
2.2716 0.05 3 1.9661
1.9397 0.06 4 1.9661
1.8659 0.08 5 1.9661
1.9903 0.09 6 1.8551
1.9031 0.11 7 1.7846
1.929 0.12 8 1.7253
0.9994 0.14 9 1.6749
1.4887 0.15 10 1.6266
1.2112 0.17 11 1.5763
1.3437 0.18 12 1.5326
1.1061 0.2 13 1.5014
1.4769 0.22 14 1.4676
1.452 0.23 15 1.4313
1.2393 0.25 16 1.3963
1.1998 0.26 17 1.3662
1.529 0.28 18 1.3353
0.949 0.29 19 1.3088
1.1857 0.31 20 1.2798
1.4852 0.32 21 1.2484
1.2845 0.34 22 1.2146
1.332 0.35 23 1.1795
0.8718 0.37 24 1.1435
1.2038 0.38 25 1.1069
1.2105 0.4 26 1.0683
0.9161 0.42 27 1.0277
1.0415 0.43 28 0.9849
1.0367 0.45 29 0.9400
0.9279 0.46 30 0.8924
0.82 0.48 31 0.8467
0.8286 0.49 32 0.8077
0.7855 0.51 33 0.7645
0.7919 0.52 34 0.7164
0.6294 0.54 35 0.6712
0.6205 0.55 36 0.6302
0.5754 0.57 37 0.5926
0.6331 0.58 38 0.5578
0.5068 0.6 39 0.5251
0.5252 0.62 40 0.5009
0.442 0.63 41 0.4800
0.4451 0.65 42 0.4628
0.3742 0.66 43 0.4491
0.8263 0.68 44 0.4383
0.4392 0.69 45 0.4277
0.5359 0.71 46 0.4174
0.3903 0.72 47 0.4051
0.4177 0.74 48 0.3921
0.4606 0.75 49 0.3792
0.5233 0.77 50 0.3700
0.3838 0.78 51 0.3638
0.353 0.8 52 0.3587
0.3108 0.82 53 0.3530
0.4029 0.83 54 0.3470
0.3425 0.85 55 0.3411
0.2976 0.86 56 0.3345
0.5347 0.88 57 0.3291
0.3208 0.89 58 0.3239
0.3319 0.91 59 0.3194
0.3333 0.92 60 0.3160
0.3102 0.94 61 0.3135
0.4149 0.95 62 0.3118
0.3044 0.97 63 0.3098
0.2688 0.98 64 0.3076
0.3926 1.0 65 0.3060
0.2969 1.02 66 0.3045
0.3799 1.03 67 0.3029
0.3045 1.05 68 0.3014
0.2295 1.06 69 0.2997
0.4113 1.08 70 0.2983
0.3093 1.09 71 0.2969
0.2542 1.11 72 0.2957
0.2445 1.12 73 0.2947
0.2592 1.14 74 0.2935
0.6259 1.15 75 0.2925
0.3217 1.17 76 0.2916
0.2969 1.18 77 0.2907
0.287 1.2 78 0.2898
0.2642 1.22 79 0.2890
0.2735 1.23 80 0.2880
0.2472 1.25 81 0.2870
0.3068 1.26 82 0.2862
0.2779 1.28 83 0.2855
0.2915 1.29 84 0.2848
0.3926 1.31 85 0.2841
0.3057 1.32 86 0.2836
0.2413 1.34 87 0.2830
0.2851 1.35 88 0.2826
0.2295 1.37 89 0.2821
0.2611 1.38 90 0.2817
0.6346 1.4 91 0.2814
0.2297 1.42 92 0.2811
0.4868 1.43 93 0.2808
0.2819 1.45 94 0.2805
0.2589 1.46 95 0.2803
0.2171 1.48 96 0.2801
0.2581 1.49 97 0.2798
0.2495 1.51 98 0.2796
0.2702 1.52 99 0.2793
0.271 1.54 100 0.2792

Framework versions

  • PEFT 0.7.2.dev0
  • Transformers 4.37.0.dev0
  • Pytorch 2.1.0+cu121
  • Datasets 2.15.0
  • Tokenizers 0.15.0