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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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- renovation |
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metrics: |
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- accuracy |
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model-index: |
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- name: vit-base-renovation |
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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: renovation |
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type: renovation |
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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: 0.6454545454545455 |
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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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# vit-base-renovation |
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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 renovation dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.1838 |
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- Accuracy: 0.6455 |
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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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| 0.9741 | 0.2 | 25 | 0.9575 | 0.4818 | |
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| 0.9827 | 0.4 | 50 | 0.9344 | 0.5182 | |
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| 0.8578 | 0.6 | 75 | 0.8343 | 0.6182 | |
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| 0.9373 | 0.81 | 100 | 0.8896 | 0.5909 | |
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| 0.7462 | 1.01 | 125 | 0.7969 | 0.6364 | |
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| 0.6953 | 1.21 | 150 | 0.8157 | 0.6364 | |
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| 0.5461 | 1.41 | 175 | 0.7634 | 0.6773 | |
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| 0.6445 | 1.61 | 200 | 0.7743 | 0.6545 | |
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| 0.5437 | 1.81 | 225 | 0.7717 | 0.65 | |
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| 0.5911 | 2.02 | 250 | 0.8339 | 0.6364 | |
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| 0.2483 | 2.22 | 275 | 0.8596 | 0.6318 | |
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| 0.378 | 2.42 | 300 | 0.9897 | 0.6182 | |
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| 0.2742 | 2.62 | 325 | 0.8965 | 0.6909 | |
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| 0.1898 | 2.82 | 350 | 1.0262 | 0.6682 | |
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| 0.2116 | 3.02 | 375 | 1.1058 | 0.6409 | |
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| 0.0702 | 3.23 | 400 | 1.0473 | 0.6545 | |
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| 0.0566 | 3.43 | 425 | 1.0962 | 0.6682 | |
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| 0.0775 | 3.63 | 450 | 1.1502 | 0.65 | |
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| 0.0485 | 3.83 | 475 | 1.1838 | 0.6455 | |
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### Framework versions |
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- Transformers 4.31.0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.2 |
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- Tokenizers 0.13.3 |
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