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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: smids_3x_beit_base_sgd_001_fold3 |
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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: test |
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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: 0.8966666666666666 |
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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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# smids_3x_beit_base_sgd_001_fold3 |
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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: 0.2937 |
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- Accuracy: 0.8967 |
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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: 0.001 |
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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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- 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: 50 |
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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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| 0.8635 | 1.0 | 225 | 0.8411 | 0.6267 | |
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| 0.6523 | 2.0 | 450 | 0.6173 | 0.7583 | |
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| 0.5403 | 3.0 | 675 | 0.5212 | 0.8017 | |
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| 0.4896 | 4.0 | 900 | 0.4692 | 0.8233 | |
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| 0.4594 | 5.0 | 1125 | 0.4353 | 0.8333 | |
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| 0.4326 | 6.0 | 1350 | 0.4063 | 0.8467 | |
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| 0.3692 | 7.0 | 1575 | 0.3897 | 0.855 | |
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| 0.4088 | 8.0 | 1800 | 0.3756 | 0.8567 | |
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| 0.4036 | 9.0 | 2025 | 0.3600 | 0.8667 | |
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| 0.387 | 10.0 | 2250 | 0.3535 | 0.8717 | |
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| 0.349 | 11.0 | 2475 | 0.3460 | 0.8717 | |
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| 0.3537 | 12.0 | 2700 | 0.3401 | 0.875 | |
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| 0.3714 | 13.0 | 2925 | 0.3342 | 0.8783 | |
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| 0.3497 | 14.0 | 3150 | 0.3327 | 0.8817 | |
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| 0.2955 | 15.0 | 3375 | 0.3234 | 0.8867 | |
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| 0.346 | 16.0 | 3600 | 0.3197 | 0.8933 | |
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| 0.3452 | 17.0 | 3825 | 0.3164 | 0.89 | |
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| 0.3182 | 18.0 | 4050 | 0.3143 | 0.8867 | |
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| 0.3047 | 19.0 | 4275 | 0.3110 | 0.8933 | |
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| 0.3008 | 20.0 | 4500 | 0.3105 | 0.8883 | |
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| 0.2783 | 21.0 | 4725 | 0.3050 | 0.8917 | |
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| 0.2751 | 22.0 | 4950 | 0.3037 | 0.8967 | |
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| 0.2477 | 23.0 | 5175 | 0.3059 | 0.8917 | |
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| 0.2485 | 24.0 | 5400 | 0.3040 | 0.8917 | |
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| 0.2841 | 25.0 | 5625 | 0.3099 | 0.8917 | |
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| 0.2803 | 26.0 | 5850 | 0.3058 | 0.8967 | |
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| 0.2313 | 27.0 | 6075 | 0.3019 | 0.8933 | |
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| 0.2302 | 28.0 | 6300 | 0.3005 | 0.895 | |
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| 0.2775 | 29.0 | 6525 | 0.2994 | 0.895 | |
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| 0.2039 | 30.0 | 6750 | 0.2961 | 0.9 | |
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| 0.261 | 31.0 | 6975 | 0.2949 | 0.9 | |
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| 0.2791 | 32.0 | 7200 | 0.2986 | 0.895 | |
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| 0.2917 | 33.0 | 7425 | 0.2938 | 0.8983 | |
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| 0.2364 | 34.0 | 7650 | 0.2966 | 0.895 | |
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| 0.2087 | 35.0 | 7875 | 0.2917 | 0.9 | |
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| 0.2544 | 36.0 | 8100 | 0.2944 | 0.8983 | |
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| 0.2254 | 37.0 | 8325 | 0.2941 | 0.8967 | |
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| 0.2119 | 38.0 | 8550 | 0.2972 | 0.8933 | |
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| 0.2445 | 39.0 | 8775 | 0.2905 | 0.9 | |
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| 0.204 | 40.0 | 9000 | 0.2909 | 0.8967 | |
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| 0.2353 | 41.0 | 9225 | 0.2968 | 0.895 | |
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| 0.2574 | 42.0 | 9450 | 0.2926 | 0.9 | |
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| 0.2197 | 43.0 | 9675 | 0.2953 | 0.8967 | |
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| 0.2519 | 44.0 | 9900 | 0.2939 | 0.8967 | |
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| 0.2337 | 45.0 | 10125 | 0.2971 | 0.895 | |
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| 0.2047 | 46.0 | 10350 | 0.2932 | 0.8967 | |
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| 0.2633 | 47.0 | 10575 | 0.2935 | 0.8967 | |
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| 0.2254 | 48.0 | 10800 | 0.2947 | 0.895 | |
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| 0.2679 | 49.0 | 11025 | 0.2937 | 0.895 | |
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| 0.2687 | 50.0 | 11250 | 0.2937 | 0.8967 | |
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### Framework versions |
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- Transformers 4.32.1 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.12.0 |
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- Tokenizers 0.13.2 |
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