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smids_1x_deit_small_rms_00001_fold1

Image Classification
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  1. README.md +125 -0
  2. model.safetensors +1 -1
  3. runs/Dec03_23-42-28_e7698b4f2488/events.out.tfevents.1701646949.e7698b4f2488.1907.6 +2 -2
README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: facebook/deit-small-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_deit_small_rms_00001_fold1
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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: 0.8848080133555927
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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_deit_small_rms_00001_fold1
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+
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+ This model is a fine-tuned version of [facebook/deit-small-patch16-224](https://huggingface.co/facebook/deit-small-patch16-224) on the imagefolder dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.7203
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+ - Accuracy: 0.8848
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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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+ | 0.4024 | 1.0 | 76 | 0.3457 | 0.8598 |
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+ | 0.2939 | 2.0 | 152 | 0.3056 | 0.8765 |
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+ | 0.1494 | 3.0 | 228 | 0.3010 | 0.8815 |
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+ | 0.1219 | 4.0 | 304 | 0.3026 | 0.8848 |
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+ | 0.0709 | 5.0 | 380 | 0.3230 | 0.8881 |
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+ | 0.0265 | 6.0 | 456 | 0.3473 | 0.8915 |
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+ | 0.0053 | 7.0 | 532 | 0.4250 | 0.8815 |
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+ | 0.0086 | 8.0 | 608 | 0.4355 | 0.8848 |
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+ | 0.0119 | 9.0 | 684 | 0.4635 | 0.8865 |
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+ | 0.0011 | 10.0 | 760 | 0.4824 | 0.8932 |
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+ | 0.0255 | 11.0 | 836 | 0.5139 | 0.8831 |
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+ | 0.0006 | 12.0 | 912 | 0.5793 | 0.8815 |
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+ | 0.0183 | 13.0 | 988 | 0.5403 | 0.8848 |
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+ | 0.0037 | 14.0 | 1064 | 0.5951 | 0.8848 |
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+ | 0.024 | 15.0 | 1140 | 0.5951 | 0.8815 |
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+ | 0.0002 | 16.0 | 1216 | 0.6061 | 0.8798 |
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+ | 0.0001 | 17.0 | 1292 | 0.5992 | 0.8948 |
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+ | 0.0157 | 18.0 | 1368 | 0.6206 | 0.8848 |
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+ | 0.0002 | 19.0 | 1444 | 0.6514 | 0.8881 |
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+ | 0.0058 | 20.0 | 1520 | 0.6656 | 0.8798 |
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+ | 0.0096 | 21.0 | 1596 | 0.6589 | 0.8915 |
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+ | 0.0045 | 22.0 | 1672 | 0.6509 | 0.8848 |
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+ | 0.0001 | 23.0 | 1748 | 0.6180 | 0.8881 |
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+ | 0.0001 | 24.0 | 1824 | 0.6676 | 0.8765 |
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+ | 0.0077 | 25.0 | 1900 | 0.6271 | 0.8831 |
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+ | 0.0032 | 26.0 | 1976 | 0.7135 | 0.8848 |
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+ | 0.0043 | 27.0 | 2052 | 0.7062 | 0.8765 |
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+ | 0.0034 | 28.0 | 2128 | 0.7064 | 0.8781 |
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+ | 0.0062 | 29.0 | 2204 | 0.6764 | 0.8781 |
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+ | 0.0001 | 30.0 | 2280 | 0.6847 | 0.8831 |
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+ | 0.006 | 31.0 | 2356 | 0.6868 | 0.8865 |
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+ | 0.009 | 32.0 | 2432 | 0.7122 | 0.8881 |
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+ | 0.0 | 33.0 | 2508 | 0.7011 | 0.8865 |
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+ | 0.0 | 34.0 | 2584 | 0.7102 | 0.8881 |
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+ | 0.0121 | 35.0 | 2660 | 0.7023 | 0.8881 |
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+ | 0.0034 | 36.0 | 2736 | 0.7188 | 0.8765 |
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+ | 0.0064 | 37.0 | 2812 | 0.7029 | 0.8848 |
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+ | 0.0001 | 38.0 | 2888 | 0.7098 | 0.8798 |
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+ | 0.0031 | 39.0 | 2964 | 0.7171 | 0.8815 |
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+ | 0.0 | 40.0 | 3040 | 0.7137 | 0.8815 |
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+ | 0.0029 | 41.0 | 3116 | 0.7143 | 0.8815 |
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+ | 0.0 | 42.0 | 3192 | 0.7224 | 0.8815 |
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+ | 0.0048 | 43.0 | 3268 | 0.7157 | 0.8831 |
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+ | 0.0 | 44.0 | 3344 | 0.7190 | 0.8848 |
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+ | 0.0 | 45.0 | 3420 | 0.7200 | 0.8848 |
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+ | 0.0 | 46.0 | 3496 | 0.7204 | 0.8848 |
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+ | 0.0 | 47.0 | 3572 | 0.7209 | 0.8848 |
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+ | 0.0024 | 48.0 | 3648 | 0.7205 | 0.8848 |
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+ | 0.0 | 49.0 | 3724 | 0.7204 | 0.8848 |
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+ | 0.0 | 50.0 | 3800 | 0.7203 | 0.8848 |
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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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