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--- |
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license: apache-2.0 |
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base_model: microsoft/beit-base-patch16-224 |
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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: beit-base-patch16-224-hasta-65-fold5 |
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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: 0.5555555555555556 |
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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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# beit-base-patch16-224-hasta-65-fold5 |
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This model is a fine-tuned version of [microsoft/beit-base-patch16-224](https://huggingface.co/microsoft/beit-base-patch16-224) on the imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.1241 |
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- Accuracy: 0.5556 |
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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: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 128 |
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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: 100 |
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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 | 0.5714 | 1 | 1.1680 | 0.3333 | |
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| No log | 1.7143 | 3 | 1.2100 | 0.1944 | |
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| No log | 2.8571 | 5 | 1.3667 | 0.2778 | |
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| No log | 4.0 | 7 | 1.1208 | 0.3889 | |
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| No log | 4.5714 | 8 | 1.1168 | 0.3611 | |
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| 1.132 | 5.7143 | 10 | 1.4031 | 0.2778 | |
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| 1.132 | 6.8571 | 12 | 1.2012 | 0.3333 | |
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| 1.132 | 8.0 | 14 | 1.2353 | 0.2778 | |
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| 1.132 | 8.5714 | 15 | 1.2099 | 0.3056 | |
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| 1.132 | 9.7143 | 17 | 1.0942 | 0.3611 | |
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| 1.132 | 10.8571 | 19 | 1.1301 | 0.4444 | |
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| 1.0271 | 12.0 | 21 | 1.0591 | 0.4167 | |
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| 1.0271 | 12.5714 | 22 | 1.0648 | 0.4444 | |
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| 1.0271 | 13.7143 | 24 | 1.1125 | 0.4722 | |
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| 1.0271 | 14.8571 | 26 | 1.1097 | 0.4722 | |
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| 1.0271 | 16.0 | 28 | 1.0616 | 0.4444 | |
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| 1.0271 | 16.5714 | 29 | 1.0284 | 0.4722 | |
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| 0.9507 | 17.7143 | 31 | 1.0291 | 0.5 | |
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| 0.9507 | 18.8571 | 33 | 1.0692 | 0.4722 | |
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| 0.9507 | 20.0 | 35 | 1.1153 | 0.5 | |
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| 0.9507 | 20.5714 | 36 | 1.1719 | 0.4444 | |
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| 0.9507 | 21.7143 | 38 | 1.0161 | 0.4444 | |
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| 0.8001 | 22.8571 | 40 | 1.1361 | 0.4444 | |
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| 0.8001 | 24.0 | 42 | 1.3277 | 0.4444 | |
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| 0.8001 | 24.5714 | 43 | 1.1331 | 0.5 | |
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| 0.8001 | 25.7143 | 45 | 1.0659 | 0.4722 | |
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| 0.8001 | 26.8571 | 47 | 1.1309 | 0.5278 | |
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| 0.8001 | 28.0 | 49 | 1.1241 | 0.5556 | |
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| 0.7175 | 28.5714 | 50 | 1.1371 | 0.5278 | |
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| 0.7175 | 29.7143 | 52 | 1.0928 | 0.5 | |
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| 0.7175 | 30.8571 | 54 | 1.2129 | 0.4444 | |
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| 0.7175 | 32.0 | 56 | 1.0321 | 0.5 | |
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| 0.7175 | 32.5714 | 57 | 1.0809 | 0.5278 | |
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| 0.7175 | 33.7143 | 59 | 0.9813 | 0.5278 | |
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| 0.6766 | 34.8571 | 61 | 1.0617 | 0.5 | |
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| 0.6766 | 36.0 | 63 | 0.9618 | 0.5278 | |
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| 0.6766 | 36.5714 | 64 | 0.9541 | 0.5556 | |
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| 0.6766 | 37.7143 | 66 | 0.9689 | 0.5278 | |
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| 0.6766 | 38.8571 | 68 | 1.1063 | 0.5556 | |
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| 0.5934 | 40.0 | 70 | 1.0139 | 0.5 | |
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| 0.5934 | 40.5714 | 71 | 1.0087 | 0.5 | |
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| 0.5934 | 41.7143 | 73 | 1.0309 | 0.5 | |
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| 0.5934 | 42.8571 | 75 | 1.0636 | 0.5 | |
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| 0.5934 | 44.0 | 77 | 1.1057 | 0.5 | |
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| 0.5934 | 44.5714 | 78 | 1.1015 | 0.4722 | |
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| 0.4926 | 45.7143 | 80 | 1.0938 | 0.5278 | |
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| 0.4926 | 46.8571 | 82 | 1.0807 | 0.5 | |
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| 0.4926 | 48.0 | 84 | 1.1275 | 0.5278 | |
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| 0.4926 | 48.5714 | 85 | 1.1604 | 0.5278 | |
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| 0.4926 | 49.7143 | 87 | 1.1296 | 0.5278 | |
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| 0.4926 | 50.8571 | 89 | 1.0748 | 0.5278 | |
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| 0.4964 | 52.0 | 91 | 1.0716 | 0.5278 | |
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| 0.4964 | 52.5714 | 92 | 1.0780 | 0.5278 | |
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| 0.4964 | 53.7143 | 94 | 1.0755 | 0.5278 | |
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| 0.4964 | 54.8571 | 96 | 1.0680 | 0.5278 | |
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| 0.4964 | 56.0 | 98 | 1.0676 | 0.5278 | |
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| 0.4964 | 56.5714 | 99 | 1.0692 | 0.5278 | |
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| 0.404 | 57.1429 | 100 | 1.0692 | 0.5278 | |
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### Framework versions |
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- Transformers 4.41.0 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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