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smids_10x_beit_large_sgd_0001_fold5

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_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: 0.8733333333333333
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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_fold5
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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: 0.3210
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+ - Accuracy: 0.8733
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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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+ | 0.9567 | 1.0 | 750 | 1.0187 | 0.4617 |
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+ | 0.813 | 2.0 | 1500 | 0.8588 | 0.6033 |
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+ | 0.7071 | 3.0 | 2250 | 0.7412 | 0.6717 |
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+ | 0.6056 | 4.0 | 3000 | 0.6548 | 0.7317 |
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+ | 0.553 | 5.0 | 3750 | 0.5916 | 0.7767 |
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+ | 0.5415 | 6.0 | 4500 | 0.5456 | 0.7983 |
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+ | 0.4714 | 7.0 | 5250 | 0.5118 | 0.8083 |
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+ | 0.4919 | 8.0 | 6000 | 0.4844 | 0.8133 |
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+ | 0.4714 | 9.0 | 6750 | 0.4633 | 0.8167 |
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+ | 0.408 | 10.0 | 7500 | 0.4458 | 0.8267 |
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+ | 0.416 | 11.0 | 8250 | 0.4326 | 0.8317 |
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+ | 0.4057 | 12.0 | 9000 | 0.4197 | 0.84 |
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+ | 0.4411 | 13.0 | 9750 | 0.4091 | 0.8383 |
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+ | 0.3787 | 14.0 | 10500 | 0.3999 | 0.84 |
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+ | 0.4112 | 15.0 | 11250 | 0.3917 | 0.8433 |
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+ | 0.3272 | 16.0 | 12000 | 0.3857 | 0.8433 |
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+ | 0.3453 | 17.0 | 12750 | 0.3795 | 0.8467 |
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+ | 0.2978 | 18.0 | 13500 | 0.3732 | 0.8467 |
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+ | 0.3695 | 19.0 | 14250 | 0.3692 | 0.8533 |
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+ | 0.3546 | 20.0 | 15000 | 0.3643 | 0.855 |
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+ | 0.3274 | 21.0 | 15750 | 0.3603 | 0.8583 |
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+ | 0.3708 | 22.0 | 16500 | 0.3566 | 0.8583 |
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+ | 0.3177 | 23.0 | 17250 | 0.3530 | 0.8617 |
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+ | 0.3259 | 24.0 | 18000 | 0.3501 | 0.865 |
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+ | 0.3343 | 25.0 | 18750 | 0.3473 | 0.8683 |
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+ | 0.3365 | 26.0 | 19500 | 0.3445 | 0.865 |
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+ | 0.2524 | 27.0 | 20250 | 0.3419 | 0.865 |
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+ | 0.3298 | 28.0 | 21000 | 0.3396 | 0.8667 |
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+ | 0.3375 | 29.0 | 21750 | 0.3374 | 0.8667 |
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+ | 0.3203 | 30.0 | 22500 | 0.3355 | 0.8683 |
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+ | 0.2843 | 31.0 | 23250 | 0.3334 | 0.8683 |
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+ | 0.3065 | 32.0 | 24000 | 0.3325 | 0.8667 |
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+ | 0.3385 | 33.0 | 24750 | 0.3310 | 0.8717 |
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+ | 0.2656 | 34.0 | 25500 | 0.3296 | 0.8717 |
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+ | 0.3103 | 35.0 | 26250 | 0.3282 | 0.8733 |
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+ | 0.3336 | 36.0 | 27000 | 0.3274 | 0.8717 |
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+ | 0.2743 | 37.0 | 27750 | 0.3265 | 0.8733 |
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+ | 0.3245 | 38.0 | 28500 | 0.3255 | 0.8717 |
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+ | 0.321 | 39.0 | 29250 | 0.3249 | 0.8733 |
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+ | 0.2652 | 40.0 | 30000 | 0.3240 | 0.8733 |
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+ | 0.2925 | 41.0 | 30750 | 0.3236 | 0.875 |
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+ | 0.3072 | 42.0 | 31500 | 0.3229 | 0.875 |
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+ | 0.3317 | 43.0 | 32250 | 0.3226 | 0.875 |
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+ | 0.2932 | 44.0 | 33000 | 0.3221 | 0.875 |
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+ | 0.3178 | 45.0 | 33750 | 0.3218 | 0.8733 |
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+ | 0.2606 | 46.0 | 34500 | 0.3214 | 0.875 |
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+ | 0.3688 | 47.0 | 35250 | 0.3212 | 0.875 |
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+ | 0.2811 | 48.0 | 36000 | 0.3211 | 0.8733 |
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+ | 0.3003 | 49.0 | 36750 | 0.3211 | 0.8733 |
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+ | 0.2418 | 50.0 | 37500 | 0.3210 | 0.8733 |
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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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