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BlacqTangent/medgemma-4b-it-sft-lora-diff

sourceHugging Faceotherupdated 11mo agoView on Hugging Face
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medgemma-4b-it-sft-lora-diff

This model is a fine-tuned version of unsloth/medgemma-4b-it-unsloth-bnb-4bit on the imagefolder dataset. It achieves the following results on the evaluation set:

  • —Loss: 0.1144

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: 0.0002
  • —trainbatchsize: 2
  • —evalbatchsize: 2
  • —seed: 42
  • —gradientaccumulationsteps: 16
  • —totaltrainbatch_size: 32
  • —optimizer: Use OptimizerNames.ADAMWTORCHFUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • —lrschedulertype: linear
  • —lrschedulerwarmup_ratio: 0.03
  • —num_epochs: 7
  • —mixedprecisiontraining: Native AMP

Training results

Training LossEpochStepValidation Loss
0.45050.133326.9109
0.4130.266745.8505
0.35240.465.0933
0.30670.533384.4616
0.2680.6667103.9022
0.23330.8123.3732
0.20060.9333142.8276
0.16691.0667162.3019
0.13491.2181.8597
0.10781.3333201.5445
0.09071.4667221.3199
0.07861.6241.1433
0.06791.7333260.9538
0.05591.8667280.8040
0.04882.0300.7037
0.04312.1333320.6440
0.03942.2667340.6086
0.03722.4360.5814
0.0362.5333380.5506
0.03352.6667400.5160
0.03152.8420.4795
0.02932.9333440.4408
0.02673.0667460.3978
0.02413.2480.3642
0.02263.3333500.3685
0.02343.4667520.3769
0.02323.6540.3629
0.02233.7333560.3403
0.02093.8667580.3231
0.01994.0600.3149
0.01944.1333620.3050
0.01874.2667640.2897
0.01774.4660.2734
0.01674.5333680.2596
0.01584.6667700.2453
0.0154.8720.2285
0.01394.9333740.2105
0.01275.0667760.1926
0.01165.2780.1769
0.01075.3333800.1634
0.00995.4667820.1505
0.00915.6840.1393
0.00835.7333860.1307
0.0085.8667880.1248
0.00776.0900.1208
0.00746.1333920.1186
0.00736.2667940.1171
0.00716.4960.1160
0.00716.5333980.1154
0.0076.66671000.1147
0.00716.81020.1146
0.0076.93331040.1144

Framework versions

  • —PEFT 0.16.0
  • —Transformers 4.57.1
  • —Pytorch 2.6.0+cu124
  • —Datasets 4.3.0
  • —Tokenizers 0.22.1