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Seed_Classifier

This model is a fine-tuned version of microsoft/dit-base on the imagefolder dataset. It achieves the following results on the evaluation set:

  • Loss: 2.6239
  • Accuracy: 0.0
  • Weighted f1: 0.0
  • Micro f1: 0.0
  • Macro f1: 0.0
  • Weighted recall: 0.0
  • Micro recall: 0.0
  • Macro recall: 0.0
  • Weighted precision: 0.0
  • Micro precision: 0.0
  • Macro precision: 0.0

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-05
  • train_batch_size: 32
  • eval_batch_size: 32
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 128
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 18

Training results

Training Loss Epoch Step Validation Loss Accuracy Weighted f1 Micro f1 Macro f1 Weighted recall Micro recall Macro recall Weighted precision Micro precision Macro precision
0.3646 1.0 1 2.4555 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.3646 2.0 2 2.4605 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.3646 3.0 3 2.6009 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.3646 4.0 4 2.7374 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.3646 5.0 5 2.7640 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.3646 6.0 6 2.7441 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.3646 7.0 7 2.7820 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.3442 8.0 8 2.8067 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.3442 9.0 9 2.8143 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.3442 10.0 10 2.7966 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.3442 11.0 11 2.7836 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.3442 12.0 12 2.7537 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.3442 13.0 13 2.7233 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.3442 14.0 14 2.6946 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.3442 15.0 15 2.6638 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.3003 16.0 16 2.6449 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.3003 17.0 17 2.6312 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.3003 18.0 18 2.6239 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

Framework versions

  • Transformers 4.44.2
  • Pytorch 2.4.1+cu121
  • Datasets 3.0.0
  • Tokenizers 0.19.1
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Evaluation results