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hushem_40x_beit_large_adamax_0001_fold1

Image Classification
Transformers
PyTorch
beit
Generated from Trainer
Eval Results
Inference Endpoints
Model card Files Community
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  1. README.md +125 -0
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README.md ADDED
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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: hushem_40x_beit_large_adamax_0001_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: 0.8888888888888888
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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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+ # hushem_40x_beit_large_adamax_0001_fold1
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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: 0.6987
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+ - Accuracy: 0.8889
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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: 0.0001
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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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+ | 0.0285 | 1.0 | 215 | 0.5849 | 0.8 |
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+ | 0.0006 | 2.0 | 430 | 0.7781 | 0.8222 |
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+ | 0.0 | 3.0 | 645 | 0.5158 | 0.8 |
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+ | 0.0 | 4.0 | 860 | 0.4099 | 0.8444 |
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+ | 0.0 | 5.0 | 1075 | 0.4040 | 0.8889 |
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+ | 0.0 | 6.0 | 1290 | 0.4087 | 0.8889 |
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+ | 0.0029 | 7.0 | 1505 | 0.2585 | 0.8889 |
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+ | 0.0159 | 8.0 | 1720 | 0.6738 | 0.9111 |
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+ | 0.0 | 9.0 | 1935 | 0.7387 | 0.8889 |
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+ | 0.0 | 10.0 | 2150 | 0.3266 | 0.9111 |
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+ | 0.0001 | 11.0 | 2365 | 0.5064 | 0.8667 |
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+ | 0.0 | 12.0 | 2580 | 0.3031 | 0.9111 |
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+ | 0.0 | 13.0 | 2795 | 0.3143 | 0.9111 |
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+ | 0.0 | 14.0 | 3010 | 0.3219 | 0.9111 |
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+ | 0.0 | 15.0 | 3225 | 0.3481 | 0.9111 |
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+ | 0.0 | 16.0 | 3440 | 0.3485 | 0.9111 |
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+ | 0.0 | 17.0 | 3655 | 0.3724 | 0.9111 |
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+ | 0.0 | 18.0 | 3870 | 0.3706 | 0.8889 |
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+ | 0.0 | 19.0 | 4085 | 0.3603 | 0.9111 |
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+ | 0.0 | 20.0 | 4300 | 0.3742 | 0.9111 |
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+ | 0.0 | 21.0 | 4515 | 0.5745 | 0.8444 |
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+ | 0.0 | 22.0 | 4730 | 0.4247 | 0.8444 |
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+ | 0.0 | 23.0 | 4945 | 0.4328 | 0.8667 |
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+ | 0.0 | 24.0 | 5160 | 0.3958 | 0.8889 |
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+ | 0.0 | 25.0 | 5375 | 0.4106 | 0.9111 |
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+ | 0.0 | 26.0 | 5590 | 0.4237 | 0.8667 |
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+ | 0.0 | 27.0 | 5805 | 0.4907 | 0.8667 |
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+ | 0.0 | 28.0 | 6020 | 0.5123 | 0.8667 |
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+ | 0.0 | 29.0 | 6235 | 0.4509 | 0.8889 |
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+ | 0.0 | 30.0 | 6450 | 0.5376 | 0.8889 |
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+ | 0.0 | 31.0 | 6665 | 0.5524 | 0.8889 |
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+ | 0.0 | 32.0 | 6880 | 0.6004 | 0.8889 |
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+ | 0.0 | 33.0 | 7095 | 0.5947 | 0.8889 |
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+ | 0.0 | 34.0 | 7310 | 0.6506 | 0.8889 |
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+ | 0.0 | 35.0 | 7525 | 0.8615 | 0.8889 |
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+ | 0.0 | 36.0 | 7740 | 0.6453 | 0.8889 |
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+ | 0.0 | 37.0 | 7955 | 0.6879 | 0.8889 |
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+ | 0.0 | 38.0 | 8170 | 0.6869 | 0.8889 |
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+ | 0.0 | 39.0 | 8385 | 0.7122 | 0.8889 |
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+ | 0.0 | 40.0 | 8600 | 0.7111 | 0.8889 |
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+ | 0.0 | 41.0 | 8815 | 0.7028 | 0.8889 |
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+ | 0.0 | 42.0 | 9030 | 0.7091 | 0.8889 |
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+ | 0.0 | 43.0 | 9245 | 0.7217 | 0.8889 |
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+ | 0.0 | 44.0 | 9460 | 0.7018 | 0.8889 |
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+ | 0.0 | 45.0 | 9675 | 0.7281 | 0.8889 |
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+ | 0.0 | 46.0 | 9890 | 0.7227 | 0.8889 |
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+ | 0.0 | 47.0 | 10105 | 0.7233 | 0.8889 |
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+ | 0.0 | 48.0 | 10320 | 0.7063 | 0.8889 |
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+ | 0.0 | 49.0 | 10535 | 0.6973 | 0.8889 |
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+ | 0.0 | 50.0 | 10750 | 0.6987 | 0.8889 |
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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 2.1.0+cu121
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+ - Datasets 2.12.0
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+ - Tokenizers 0.13.2
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