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--- |
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license: apache-2.0 |
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base_model: microsoft/cvt-13 |
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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: cvt-13 |
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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: 0.9886363636363636 |
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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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# cvt-13 |
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This model is a fine-tuned version of [microsoft/cvt-13](https://huggingface.co/microsoft/cvt-13) on the imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0361 |
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- Accuracy: 0.9886 |
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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-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 32 |
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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: 15 |
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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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| 0.4048 | 1.0 | 327 | 0.2161 | 0.9156 | |
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| 0.33 | 2.0 | 654 | 0.1320 | 0.9501 | |
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| 0.3147 | 3.0 | 981 | 0.1060 | 0.9612 | |
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| 0.2213 | 4.0 | 1309 | 0.0820 | 0.9742 | |
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| 0.3256 | 5.0 | 1636 | 0.0717 | 0.9750 | |
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| 0.3207 | 6.0 | 1963 | 0.1062 | 0.9626 | |
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| 0.2273 | 7.0 | 2290 | 0.0535 | 0.9797 | |
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| 0.2066 | 8.0 | 2618 | 0.0566 | 0.9817 | |
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| 0.2162 | 9.0 | 2945 | 0.0459 | 0.9828 | |
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| 0.2296 | 10.0 | 3272 | 0.0444 | 0.9851 | |
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| 0.187 | 11.0 | 3599 | 0.0348 | 0.9882 | |
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| 0.2208 | 12.0 | 3927 | 0.0505 | 0.9848 | |
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| 0.1855 | 13.0 | 4254 | 0.0371 | 0.9869 | |
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| 0.1875 | 14.0 | 4581 | 0.0384 | 0.9880 | |
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| 0.202 | 14.99 | 4905 | 0.0361 | 0.9886 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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