Seed_Classifier_V2 / README.md
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metadata
library_name: transformers
base_model: microsoft/dit-base
tags:
  - generated_from_trainer
datasets:
  - imagefolder
metrics:
  - accuracy
model-index:
  - name: Seed_Classifier_V2
    results:
      - task:
          name: Image Classification
          type: image-classification
        dataset:
          name: imagefolder
          type: imagefolder
          config: default
          split: train
          args: default
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0

Seed_Classifier_V2

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: 1.6985
  • 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
0.3829 1.0 1 1.0584 0.5 0.3333 0.5 0.3333 0.5 0.5 0.5 0.25 0.5 0.25
0.3829 2.0 2 1.2877 0.25 0.2 0.25 0.2 0.25 0.25 0.25 0.1667 0.25 0.1667
0.3829 3.0 3 2.2985 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.3829 4.0 4 2.4998 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.3829 5.0 5 2.2230 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.3829 6.0 6 1.9467 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.3829 7.0 7 1.7201 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.3628 8.0 8 1.5736 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.3628 9.0 9 1.5412 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.3628 10.0 10 1.5484 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.3628 11.0 11 1.5762 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.3628 12.0 12 1.5907 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.3628 13.0 13 1.6231 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.3628 14.0 14 1.6462 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.3628 15.0 15 1.6710 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.3175 16.0 16 1.6883 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.3175 17.0 17 1.6994 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
0.3175 18.0 18 1.6985 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