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--- |
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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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- 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: Tb_Dataset |
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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: validation |
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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: 0.875 |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# Tb_Dataset |
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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: 0.4037 |
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- Accuracy: 0.875 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.0002 |
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- train_batch_size: 16 |
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- eval_batch_size: 8 |
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- seed: 42 |
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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: 4 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:------:|:----:|:---------------:|:--------:| |
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| 0.0996 | 0.3067 | 100 | 1.0429 | 0.5625 | |
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| 0.0481 | 0.6135 | 200 | 0.5665 | 0.8125 | |
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| 0.0391 | 0.9202 | 300 | 1.0037 | 0.6875 | |
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| 0.0711 | 1.2270 | 400 | 0.5200 | 0.875 | |
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| 0.0258 | 1.5337 | 500 | 0.3818 | 0.9375 | |
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| 0.0547 | 1.8405 | 600 | 0.3415 | 0.9375 | |
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| 0.0029 | 2.1472 | 700 | 0.0637 | 0.9375 | |
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| 0.0543 | 2.4540 | 800 | 0.7362 | 0.8125 | |
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| 0.0265 | 2.7607 | 900 | 1.0917 | 0.75 | |
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| 0.0017 | 3.0675 | 1000 | 0.0030 | 1.0 | |
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| 0.0054 | 3.3742 | 1100 | 0.0364 | 1.0 | |
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| 0.0234 | 3.6810 | 1200 | 0.2310 | 0.875 | |
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| 0.0076 | 3.9877 | 1300 | 0.4037 | 0.875 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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