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smids_10x_beit_large_sgd_0001_fold3

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_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: 0.8783333333333333
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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_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: 0.3045
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+ - Accuracy: 0.8783
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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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+ | 0.9373 | 1.0 | 750 | 1.0091 | 0.4617 |
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+ | 0.7639 | 2.0 | 1500 | 0.8536 | 0.6117 |
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+ | 0.6803 | 3.0 | 2250 | 0.7396 | 0.6933 |
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+ | 0.5905 | 4.0 | 3000 | 0.6588 | 0.75 |
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+ | 0.5735 | 5.0 | 3750 | 0.5968 | 0.7833 |
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+ | 0.5021 | 6.0 | 4500 | 0.5507 | 0.8017 |
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+ | 0.4704 | 7.0 | 5250 | 0.5159 | 0.8133 |
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+ | 0.4872 | 8.0 | 6000 | 0.4878 | 0.8267 |
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+ | 0.4458 | 9.0 | 6750 | 0.4650 | 0.83 |
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+ | 0.4154 | 10.0 | 7500 | 0.4469 | 0.8417 |
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+ | 0.4321 | 11.0 | 8250 | 0.4318 | 0.845 |
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+ | 0.3944 | 12.0 | 9000 | 0.4172 | 0.8433 |
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+ | 0.3976 | 13.0 | 9750 | 0.4054 | 0.8483 |
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+ | 0.4242 | 14.0 | 10500 | 0.3948 | 0.85 |
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+ | 0.3817 | 15.0 | 11250 | 0.3850 | 0.8517 |
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+ | 0.3695 | 16.0 | 12000 | 0.3777 | 0.8517 |
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+ | 0.3394 | 17.0 | 12750 | 0.3711 | 0.8533 |
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+ | 0.3418 | 18.0 | 13500 | 0.3639 | 0.8583 |
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+ | 0.3927 | 19.0 | 14250 | 0.3584 | 0.8633 |
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+ | 0.3355 | 20.0 | 15000 | 0.3536 | 0.8617 |
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+ | 0.3182 | 21.0 | 15750 | 0.3485 | 0.86 |
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+ | 0.3252 | 22.0 | 16500 | 0.3442 | 0.8617 |
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+ | 0.3481 | 23.0 | 17250 | 0.3402 | 0.86 |
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+ | 0.352 | 24.0 | 18000 | 0.3367 | 0.8617 |
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+ | 0.3814 | 25.0 | 18750 | 0.3335 | 0.865 |
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+ | 0.3436 | 26.0 | 19500 | 0.3305 | 0.865 |
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+ | 0.2353 | 27.0 | 20250 | 0.3280 | 0.865 |
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+ | 0.3097 | 28.0 | 21000 | 0.3253 | 0.8683 |
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+ | 0.3673 | 29.0 | 21750 | 0.3232 | 0.8683 |
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+ | 0.316 | 30.0 | 22500 | 0.3211 | 0.87 |
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+ | 0.2736 | 31.0 | 23250 | 0.3193 | 0.8733 |
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+ | 0.3111 | 32.0 | 24000 | 0.3172 | 0.875 |
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+ | 0.3586 | 33.0 | 24750 | 0.3157 | 0.875 |
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+ | 0.3482 | 34.0 | 25500 | 0.3143 | 0.875 |
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+ | 0.2894 | 35.0 | 26250 | 0.3130 | 0.875 |
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+ | 0.3247 | 36.0 | 27000 | 0.3121 | 0.8733 |
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+ | 0.3266 | 37.0 | 27750 | 0.3109 | 0.8733 |
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+ | 0.3501 | 38.0 | 28500 | 0.3098 | 0.8733 |
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+ | 0.3018 | 39.0 | 29250 | 0.3089 | 0.875 |
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+ | 0.3416 | 40.0 | 30000 | 0.3082 | 0.875 |
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+ | 0.318 | 41.0 | 30750 | 0.3074 | 0.875 |
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+ | 0.3558 | 42.0 | 31500 | 0.3067 | 0.8767 |
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+ | 0.2993 | 43.0 | 32250 | 0.3061 | 0.8767 |
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+ | 0.2907 | 44.0 | 33000 | 0.3056 | 0.8767 |
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+ | 0.2783 | 45.0 | 33750 | 0.3053 | 0.8767 |
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+ | 0.2937 | 46.0 | 34500 | 0.3050 | 0.8767 |
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+ | 0.3037 | 47.0 | 35250 | 0.3048 | 0.8783 |
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+ | 0.3233 | 48.0 | 36000 | 0.3046 | 0.8783 |
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+ | 0.3074 | 49.0 | 36750 | 0.3045 | 0.8783 |
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+ | 0.2861 | 50.0 | 37500 | 0.3045 | 0.8783 |
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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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