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metadata
library_name: transformers
license: apache-2.0
base_model: facebook/convnext-small-224
tags:
  - image-classification
  - vision
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: Validated_Balanced_Raw_Data_model_boost8
    results: []

Validated_Balanced_Raw_Data_model_boost8

This model is a fine-tuned version of facebook/convnext-small-224 on the Logiroad/Validated_Balanced_Raw_Dataset dataset. It achieves the following results on the evaluation set:

  • Loss: 1.1054
  • Accuracy: 0.5425

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: 3e-05
  • train_batch_size: 8
  • eval_batch_size: 16
  • seed: 1337
  • optimizer: Use OptimizerNames.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_ratio: 0.05
  • num_epochs: 25
  • mixed_precision_training: Native AMP
  • label_smoothing_factor: 0.05

Training results

Training Loss Epoch Step Validation Loss Accuracy
1.326 1.0 80 1.2990 0.3868
1.2698 2.0 160 1.2875 0.3726
1.2271 3.0 240 1.2136 0.4245
1.1742 4.0 320 1.1844 0.4717
1.1507 5.0 400 1.1472 0.4906
1.1228 6.0 480 1.1568 0.4623
1.0484 7.0 560 1.1222 0.4811
1.0224 8.0 640 1.1054 0.5425
0.9876 9.0 720 1.1333 0.5
0.9897 10.0 800 1.1368 0.4811
0.9133 11.0 880 1.0923 0.5
0.8814 12.0 960 1.1101 0.4717
0.8185 13.0 1040 1.1416 0.4953
0.7917 14.0 1120 1.1237 0.5047
0.7773 15.0 1200 1.0994 0.5047
0.7289 16.0 1280 1.1059 0.5094
0.7337 17.0 1360 1.1085 0.5142
0.7052 18.0 1440 1.1131 0.5189
0.6703 19.0 1520 1.1068 0.5330
0.6482 20.0 1600 1.1251 0.5189
0.6421 21.0 1680 1.1164 0.5283
0.6738 22.0 1760 1.1147 0.5377
0.6459 23.0 1840 1.1152 0.5283
0.6302 24.0 1920 1.1156 0.5283
0.689 25.0 2000 1.1157 0.5283

Framework versions

  • Transformers 4.46.1
  • Pytorch 2.3.0
  • Datasets 3.1.0
  • Tokenizers 0.20.3