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hushem_1x_deit_tiny_adamax_lr00001_fold1

Image Classification
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metadata
license: apache-2.0
base_model: facebook/deit-tiny-patch16-224
tags:
  - generated_from_trainer
datasets:
  - imagefolder
metrics:
  - accuracy
model-index:
  - name: hushem_1x_deit_tiny_adamax_lr00001_fold1
    results:
      - task:
          name: Image Classification
          type: image-classification
        dataset:
          name: imagefolder
          type: imagefolder
          config: default
          split: test
          args: default
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.4222222222222222

hushem_1x_deit_tiny_adamax_lr00001_fold1

This model is a fine-tuned version of facebook/deit-tiny-patch16-224 on the imagefolder dataset. It achieves the following results on the evaluation set:

  • Loss: 1.3005
  • Accuracy: 0.4222

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: 1e-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: 50

Training results

Training Loss Epoch Step Validation Loss Accuracy
No log 0.67 1 1.4838 0.2222
No log 2.0 3 1.4436 0.2222
No log 2.67 4 1.4334 0.1778
No log 4.0 6 1.4190 0.2667
No log 4.67 7 1.4121 0.2889
No log 6.0 9 1.3991 0.3111
1.3869 6.67 10 1.3926 0.3333
1.3869 8.0 12 1.3807 0.3556
1.3869 8.67 13 1.3748 0.3556
1.3869 10.0 15 1.3643 0.3778
1.3869 10.67 16 1.3598 0.3778
1.3869 12.0 18 1.3511 0.4
1.3869 12.67 19 1.3478 0.3778
1.1228 14.0 21 1.3405 0.4
1.1228 14.67 22 1.3380 0.4
1.1228 16.0 24 1.3323 0.4222
1.1228 16.67 25 1.3292 0.4222
1.1228 18.0 27 1.3250 0.4222
1.1228 18.67 28 1.3231 0.4222
0.9505 20.0 30 1.3201 0.4222
0.9505 20.67 31 1.3189 0.4222
0.9505 22.0 33 1.3162 0.4222
0.9505 22.67 34 1.3147 0.4222
0.9505 24.0 36 1.3120 0.4222
0.9505 24.67 37 1.3113 0.4222
0.9505 26.0 39 1.3090 0.4222
0.8411 26.67 40 1.3078 0.4222
0.8411 28.0 42 1.3057 0.4222
0.8411 28.67 43 1.3047 0.4222
0.8411 30.0 45 1.3028 0.4222
0.8411 30.67 46 1.3020 0.4222
0.8411 32.0 48 1.3010 0.4222
0.8411 32.67 49 1.3007 0.4222
0.7881 33.33 50 1.3005 0.4222

Framework versions

  • Transformers 4.35.0
  • Pytorch 2.1.0+cu118
  • Datasets 2.14.6
  • Tokenizers 0.14.1