| | ---
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| | library_name: transformers
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| | license: apache-2.0
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| | base_model: google/vit-base-patch16-224-in21k
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| | tags:
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| | - image-classification
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| | - vision
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| | - generated_from_trainer
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| | datasets:
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| | - imagefolder
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| | metrics:
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| | - accuracy
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| | model-index:
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| | - name: TransparentBagClassifier
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| | results:
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| | - task:
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| | name: Image Classification
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| | type: image-classification
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| | dataset:
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| | name: imagefolder
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| | type: imagefolder
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| | config: default
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| | split: train
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| | args: default
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| | metrics:
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| | - name: Accuracy
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| | type: accuracy
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| | value: 0.9955156950672646
|
| | ---
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| |
|
| | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
| | should probably proofread and complete it, then remove this comment. -->
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| |
|
| | # TransparentBagClassifier
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| |
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| | This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the imagefolder dataset.
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| | It achieves the following results on the evaluation set:
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| | - Loss: 0.0411
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| | - Accuracy: 0.9955
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| |
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| | ## Model description
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| |
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| | More information needed
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| |
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| | ## Intended uses & limitations
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| |
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| | More information needed
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| |
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| | ## Training and evaluation data
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| |
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| | More information needed
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| |
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| | ## Training procedure
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| |
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| | ### Training hyperparameters
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| |
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| | The following hyperparameters were used during training:
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| | - learning_rate: 2e-05
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| | - train_batch_size: 8
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| | - eval_batch_size: 8
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| | - seed: 1337
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| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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| | - lr_scheduler_type: linear
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| | - num_epochs: 5.0
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| |
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| | ### Training results
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| |
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| | | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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| | |:-------------:|:-----:|:----:|:---------------:|:--------:|
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| | | 0.0694 | 1.0 | 158 | 0.0719 | 0.9821 |
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| | | 0.0871 | 2.0 | 316 | 0.0411 | 0.9955 |
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| | | 0.0561 | 3.0 | 474 | 0.0419 | 0.9910 |
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| | | 0.0673 | 4.0 | 632 | 0.0424 | 0.9865 |
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| | | 0.0099 | 5.0 | 790 | 0.0517 | 0.9821 |
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| |
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| |
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| | ### Framework versions
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| |
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| | - Transformers 4.44.2
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| | - Pytorch 2.4.1+cpu
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| | - Datasets 3.0.0
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| | - Tokenizers 0.19.1
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| |
|
