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--- |
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license: apache-2.0 |
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base_model: microsoft/swinv2-base-patch4-window8-256 |
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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: vit-base-patch16-224 |
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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: 0.7209302325581395 |
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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-patch16-224 |
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This model is a fine-tuned version of [microsoft/swinv2-base-patch4-window8-256](https://huggingface.co/microsoft/swinv2-base-patch4-window8-256) on the imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5932 |
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- Accuracy: 0.7209 |
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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: 5e-06 |
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- train_batch_size: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 16 |
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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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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 10 |
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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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| No log | 0.96 | 6 | 0.7424 | 0.3488 | |
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| 0.7374 | 1.92 | 12 | 0.5932 | 0.7209 | |
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| 0.7374 | 2.88 | 18 | 0.5843 | 0.7209 | |
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| 0.5783 | 4.0 | 25 | 0.5996 | 0.7209 | |
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| 0.5358 | 4.96 | 31 | 0.6147 | 0.7209 | |
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| 0.5358 | 5.92 | 37 | 0.6159 | 0.7209 | |
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| 0.5745 | 6.88 | 43 | 0.6091 | 0.7209 | |
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| 0.5325 | 8.0 | 50 | 0.6067 | 0.7209 | |
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| 0.5325 | 8.96 | 56 | 0.6047 | 0.7209 | |
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| 0.524 | 9.6 | 60 | 0.6046 | 0.7209 | |
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### Framework versions |
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- Transformers 4.42.3 |
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- Pytorch 2.3.1+cu118 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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