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smids_10x_beit_large_sgd_0001_fold4

Image Classification
Transformers
PyTorch
beit
Generated from Trainer
Eval Results
Inference Endpoints
Model card Files Community
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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: smids_10x_beit_large_sgd_0001_fold4
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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: 0.8583333333333333
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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_10x_beit_large_sgd_0001_fold4
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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: 0.3577
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+ - Accuracy: 0.8583
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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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+ | 0.956 | 1.0 | 750 | 0.9742 | 0.4667 |
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+ | 0.7783 | 2.0 | 1500 | 0.8200 | 0.63 |
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+ | 0.7323 | 3.0 | 2250 | 0.7096 | 0.71 |
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+ | 0.6337 | 4.0 | 3000 | 0.6341 | 0.7517 |
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+ | 0.5065 | 5.0 | 3750 | 0.5795 | 0.775 |
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+ | 0.4965 | 6.0 | 4500 | 0.5386 | 0.8 |
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+ | 0.4578 | 7.0 | 5250 | 0.5091 | 0.8117 |
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+ | 0.4692 | 8.0 | 6000 | 0.4857 | 0.825 |
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+ | 0.4711 | 9.0 | 6750 | 0.4676 | 0.8333 |
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+ | 0.3709 | 10.0 | 7500 | 0.4525 | 0.835 |
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+ | 0.4051 | 11.0 | 8250 | 0.4402 | 0.8367 |
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+ | 0.4533 | 12.0 | 9000 | 0.4305 | 0.8417 |
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+ | 0.3537 | 13.0 | 9750 | 0.4215 | 0.8467 |
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+ | 0.4025 | 14.0 | 10500 | 0.4147 | 0.8483 |
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+ | 0.3254 | 15.0 | 11250 | 0.4082 | 0.8467 |
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+ | 0.3312 | 16.0 | 12000 | 0.4031 | 0.8467 |
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+ | 0.2854 | 17.0 | 12750 | 0.3983 | 0.8483 |
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+ | 0.3355 | 18.0 | 13500 | 0.3942 | 0.8517 |
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+ | 0.3881 | 19.0 | 14250 | 0.3905 | 0.8483 |
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+ | 0.3257 | 20.0 | 15000 | 0.3873 | 0.8517 |
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+ | 0.3303 | 21.0 | 15750 | 0.3846 | 0.8483 |
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+ | 0.3308 | 22.0 | 16500 | 0.3815 | 0.8517 |
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+ | 0.3025 | 23.0 | 17250 | 0.3791 | 0.85 |
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+ | 0.3591 | 24.0 | 18000 | 0.3770 | 0.8517 |
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+ | 0.3426 | 25.0 | 18750 | 0.3750 | 0.8567 |
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+ | 0.2909 | 26.0 | 19500 | 0.3737 | 0.8567 |
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+ | 0.3106 | 27.0 | 20250 | 0.3719 | 0.855 |
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+ | 0.3129 | 28.0 | 21000 | 0.3704 | 0.855 |
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+ | 0.2957 | 29.0 | 21750 | 0.3688 | 0.855 |
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+ | 0.2639 | 30.0 | 22500 | 0.3673 | 0.855 |
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+ | 0.2821 | 31.0 | 23250 | 0.3660 | 0.855 |
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+ | 0.2912 | 32.0 | 24000 | 0.3649 | 0.8567 |
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+ | 0.3006 | 33.0 | 24750 | 0.3640 | 0.8583 |
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+ | 0.3129 | 34.0 | 25500 | 0.3632 | 0.8583 |
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+ | 0.2463 | 35.0 | 26250 | 0.3625 | 0.86 |
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+ | 0.3133 | 36.0 | 27000 | 0.3619 | 0.8583 |
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+ | 0.3061 | 37.0 | 27750 | 0.3612 | 0.8583 |
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+ | 0.3206 | 38.0 | 28500 | 0.3606 | 0.8583 |
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+ | 0.3433 | 39.0 | 29250 | 0.3601 | 0.8583 |
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+ | 0.3138 | 40.0 | 30000 | 0.3597 | 0.8583 |
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+ | 0.2988 | 41.0 | 30750 | 0.3593 | 0.8583 |
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+ | 0.3075 | 42.0 | 31500 | 0.3589 | 0.8583 |
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+ | 0.3059 | 43.0 | 32250 | 0.3587 | 0.8583 |
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+ | 0.3142 | 44.0 | 33000 | 0.3585 | 0.8583 |
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+ | 0.3034 | 45.0 | 33750 | 0.3583 | 0.8583 |
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+ | 0.2744 | 46.0 | 34500 | 0.3580 | 0.8583 |
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+ | 0.2599 | 47.0 | 35250 | 0.3579 | 0.8583 |
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+ | 0.2643 | 48.0 | 36000 | 0.3578 | 0.8583 |
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+ | 0.2927 | 49.0 | 36750 | 0.3577 | 0.8583 |
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+ | 0.2381 | 50.0 | 37500 | 0.3577 | 0.8583 |
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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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