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yalhessi/lemexp-task1-min_symbols_template_small-deepseek-coder-1.3b-base-ddp-12lr

sourceHugging Faceotherupdated 2y agoView on Hugging Face
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Model Card

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lemexp-task1-minsymbolstemplate_small-deepseek-coder-1.3b-base-ddp-12lr

This model is a fine-tuned version of deepseek-ai/deepseek-coder-1.3b-base on an unknown dataset. It achieves the following results on the evaluation set:

  • —Loss: 0.1883

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: 0.0012
  • —trainbatchsize: 2
  • —evalbatchsize: 2
  • —seed: 42
  • —distributed_type: multi-GPU
  • —num_devices: 8
  • —totaltrainbatch_size: 16
  • —totalevalbatch_size: 16
  • —optimizer: Use OptimizerNames.ADAMWTORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizerargs=No additional optimizer arguments
  • —lrschedulertype: linear
  • —num_epochs: 12
  • —mixedprecisiontraining: Native AMP

Training results

Training LossEpochStepValidation Loss
0.46090.20016290.3805
0.3750.400112580.3388
0.35680.600218870.3382
0.33330.800325160.3202
0.32681.000331450.3155
0.31431.200437740.3031
0.30861.400444030.2994
0.30161.600550320.2918
0.29981.800656610.2850
0.29252.000662900.2894
0.29142.200769190.2819
0.28452.400875480.2798
0.28052.600881770.2719
0.27942.800988060.2709
0.2773.001094350.2721
0.26293.2010100640.2637
0.26473.4011106930.2616
0.2623.6011113220.2602
0.26043.8012119510.2553
0.25734.0013125800.2573
0.24714.2013132090.2583
0.24444.4014138380.2479
0.24864.6015144670.2466
0.24194.8015150960.2497
0.24025.0016157250.2444
0.23315.2017163540.2394
0.23045.4017169830.2373
0.2275.6018176120.2367
0.22445.8018182410.2306
0.22536.0019188700.2269
0.21966.2020194990.2221
0.2096.4020201280.2237
0.21016.6021207570.2236
0.20666.8022213860.2186
0.20957.0022220150.2159
0.19337.2023226440.2144
0.19377.4024232730.2134
0.19317.6024239020.2154
0.19177.8025245310.2085
0.18898.0025251600.2077
0.17678.2026257890.2079
0.17698.4027264180.2033
0.17598.6027270470.1997
0.17358.8028276760.1973
0.17519.0029283050.1951
0.16589.2029289340.1975
0.15819.4030295630.1956
0.15759.6031301920.1923
0.15739.8031308210.1896
0.155810.0032314500.1931
0.140310.2032320790.1932
0.140210.4033327080.1900
0.139610.6034333370.1894
0.139510.8034339660.1881
0.136711.0035345950.1879
0.126911.2036352240.1918
0.123311.4036358530.1899
0.122611.6037364820.1893
0.121211.8038371110.1883

Framework versions

  • —PEFT 0.14.0
  • —Transformers 4.47.0
  • —Pytorch 2.5.1+cu124
  • —Datasets 3.2.0
  • —Tokenizers 0.21.0