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smids_1x_beit_base_rms_00001_fold5

Image Classification
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  1. README.md +125 -0
  2. model.safetensors +1 -1
  3. runs/Dec01_09-51-46_1242d03470a0/events.out.tfevents.1701424308.1242d03470a0.3093.6 +2 -2
README.md ADDED
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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_1x_beit_base_rms_00001_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: 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: 0.895
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+ ---
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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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+
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+ # smids_1x_beit_base_rms_00001_fold5
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+
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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: 0.9075
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+ - Accuracy: 0.895
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 1e-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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+ - 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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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 0.3429 | 1.0 | 75 | 0.3196 | 0.8817 |
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+ | 0.2319 | 2.0 | 150 | 0.2825 | 0.8883 |
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+ | 0.1642 | 3.0 | 225 | 0.2956 | 0.8883 |
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+ | 0.0613 | 4.0 | 300 | 0.2991 | 0.905 |
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+ | 0.0375 | 5.0 | 375 | 0.4173 | 0.89 |
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+ | 0.0392 | 6.0 | 450 | 0.4376 | 0.895 |
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+ | 0.0266 | 7.0 | 525 | 0.5591 | 0.8933 |
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+ | 0.0211 | 8.0 | 600 | 0.6357 | 0.8883 |
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+ | 0.0129 | 9.0 | 675 | 0.5589 | 0.8967 |
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+ | 0.039 | 10.0 | 750 | 0.6087 | 0.8933 |
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+ | 0.0196 | 11.0 | 825 | 0.6853 | 0.8967 |
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+ | 0.0875 | 12.0 | 900 | 0.6905 | 0.8833 |
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+ | 0.0161 | 13.0 | 975 | 0.7505 | 0.8867 |
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+ | 0.0005 | 14.0 | 1050 | 0.7592 | 0.875 |
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+ | 0.0258 | 15.0 | 1125 | 0.7859 | 0.8783 |
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+ | 0.0008 | 16.0 | 1200 | 0.7624 | 0.8783 |
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+ | 0.0078 | 17.0 | 1275 | 0.7129 | 0.8917 |
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+ | 0.0151 | 18.0 | 1350 | 0.7730 | 0.885 |
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+ | 0.015 | 19.0 | 1425 | 0.7612 | 0.88 |
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+ | 0.0036 | 20.0 | 1500 | 0.7765 | 0.89 |
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+ | 0.0036 | 21.0 | 1575 | 0.7746 | 0.89 |
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+ | 0.0163 | 22.0 | 1650 | 0.7920 | 0.88 |
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+ | 0.0002 | 23.0 | 1725 | 0.7971 | 0.8867 |
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+ | 0.0013 | 24.0 | 1800 | 0.8091 | 0.8833 |
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+ | 0.0084 | 25.0 | 1875 | 0.8422 | 0.8817 |
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+ | 0.0077 | 26.0 | 1950 | 0.8718 | 0.89 |
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+ | 0.0059 | 27.0 | 2025 | 0.8359 | 0.89 |
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+ | 0.0135 | 28.0 | 2100 | 0.8777 | 0.8833 |
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+ | 0.0007 | 29.0 | 2175 | 0.8422 | 0.895 |
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+ | 0.0059 | 30.0 | 2250 | 0.8920 | 0.8933 |
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+ | 0.0039 | 31.0 | 2325 | 0.9311 | 0.875 |
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+ | 0.0027 | 32.0 | 2400 | 0.8796 | 0.89 |
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+ | 0.0001 | 33.0 | 2475 | 0.9632 | 0.88 |
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+ | 0.0031 | 34.0 | 2550 | 0.8453 | 0.89 |
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+ | 0.0036 | 35.0 | 2625 | 0.8275 | 0.895 |
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+ | 0.003 | 36.0 | 2700 | 0.8573 | 0.8883 |
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+ | 0.0273 | 37.0 | 2775 | 0.8009 | 0.8967 |
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+ | 0.0042 | 38.0 | 2850 | 0.8716 | 0.8917 |
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+ | 0.0032 | 39.0 | 2925 | 0.9439 | 0.88 |
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+ | 0.0005 | 40.0 | 3000 | 0.8577 | 0.8917 |
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+ | 0.0023 | 41.0 | 3075 | 0.8426 | 0.8867 |
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+ | 0.0083 | 42.0 | 3150 | 0.8441 | 0.895 |
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+ | 0.0 | 43.0 | 3225 | 0.8722 | 0.8883 |
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+ | 0.0036 | 44.0 | 3300 | 0.8679 | 0.8883 |
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+ | 0.0009 | 45.0 | 3375 | 0.9113 | 0.8917 |
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+ | 0.0131 | 46.0 | 3450 | 0.8965 | 0.89 |
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+ | 0.0 | 47.0 | 3525 | 0.8892 | 0.8933 |
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+ | 0.0001 | 48.0 | 3600 | 0.9072 | 0.8933 |
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+ | 0.0024 | 49.0 | 3675 | 0.9074 | 0.8933 |
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+ | 0.0054 | 50.0 | 3750 | 0.9075 | 0.895 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.35.2
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+ - Pytorch 2.1.0+cu118
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+ - Datasets 2.15.0
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+ - Tokenizers 0.15.0
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