| | ---
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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: 0.8597560975609756
|
| | ---
|
| |
|
| | <!-- 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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| |
|
| | 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: 0.3956
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| | - Accuracy: 0.8598
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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 | Accuracy | Validation Loss |
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| | |:-------------:|:-----:|:----:|:--------:|:---------------:|
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| | | 0.448 | 1.0 | 82 | 0.7304 | 0.5725 |
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| | | 0.5097 | 2.0 | 164 | 0.7652 | 0.4946 |
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| | | 0.452 | 3.0 | 246 | 0.7565 | 0.4841 |
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| | | 0.3885 | 4.0 | 328 | 0.7565 | 0.4812 |
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| | | 0.4743 | 5.0 | 410 | 0.7739 | 0.4626 |
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| | | 0.4749 | 4.0 | 464 | 0.4572 | 0.7988 |
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| | | 0.4319 | 5.0 | 580 | 0.3956 | 0.8598 |
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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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| |
|
