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+ ---
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+ license: apache-2.0
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+ base_model: microsoft/beit-large-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: Karma_3Class_RMSprop_1e5_20Epoch_Beit-large-224_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: 0.8553936450111314
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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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+ # Karma_3Class_RMSprop_1e5_20Epoch_Beit-large-224_fold3
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+
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+ This model is a fine-tuned version of [microsoft/beit-large-patch16-224](https://huggingface.co/microsoft/beit-large-patch16-224) on the imagefolder dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.7383
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+ - Accuracy: 0.8554
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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: 16
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+ - eval_batch_size: 16
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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: 10
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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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+ | 0.4248 | 1.0 | 2467 | 0.4024 | 0.8380 |
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+ | 0.3093 | 2.0 | 4934 | 0.3847 | 0.8552 |
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+ | 0.1192 | 3.0 | 7401 | 0.5222 | 0.8533 |
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+ | 0.1199 | 4.0 | 9868 | 0.6854 | 0.8465 |
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+ | 0.1174 | 5.0 | 12335 | 0.9930 | 0.8524 |
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+ | 0.0001 | 6.0 | 14802 | 1.3492 | 0.8527 |
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+ | 0.0001 | 7.0 | 17269 | 1.4598 | 0.8496 |
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+ | 0.0667 | 8.0 | 19736 | 1.6952 | 0.8483 |
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+ | 0.0022 | 9.0 | 22203 | 1.6924 | 0.8546 |
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+ | 0.0175 | 10.0 | 24670 | 1.7383 | 0.8554 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.32.1
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+ - Pytorch 2.0.1
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+ - Datasets 2.12.0
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+ - Tokenizers 0.13.2