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vit-base-patch16-224-ve-U13-b-80

Image Classification
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vit
Generated from Trainer
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  2. model.safetensors +1 -1
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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: google/vit-base-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: vit-base-patch16-224-ve-U13-b-80
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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: validation
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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: 0.8260869565217391
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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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+ # vit-base-patch16-224-ve-U13-b-80
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+
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+ This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the imagefolder dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.7603
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+ - Accuracy: 0.8261
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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: 5.5e-05
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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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+ - gradient_accumulation_steps: 4
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+ - total_train_batch_size: 128
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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: 0.05
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+ - num_epochs: 80
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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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+ | No log | 0.92 | 6 | 1.3848 | 0.3478 |
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+ | 1.3848 | 2.0 | 13 | 1.3692 | 0.5217 |
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+ | 1.3848 | 2.92 | 19 | 1.3184 | 0.5870 |
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+ | 1.352 | 4.0 | 26 | 1.2217 | 0.4565 |
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+ | 1.2316 | 4.92 | 32 | 1.1418 | 0.4783 |
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+ | 1.2316 | 6.0 | 39 | 1.0689 | 0.4783 |
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+ | 1.0849 | 6.92 | 45 | 0.9931 | 0.5870 |
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+ | 0.9314 | 8.0 | 52 | 0.9458 | 0.6957 |
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+ | 0.9314 | 8.92 | 58 | 0.8675 | 0.6957 |
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+ | 0.8001 | 10.0 | 65 | 0.8148 | 0.7174 |
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+ | 0.6493 | 10.92 | 71 | 0.7692 | 0.7609 |
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+ | 0.6493 | 12.0 | 78 | 0.6428 | 0.8043 |
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+ | 0.5145 | 12.92 | 84 | 0.6025 | 0.8261 |
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+ | 0.379 | 14.0 | 91 | 0.5621 | 0.8043 |
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+ | 0.379 | 14.92 | 97 | 0.5298 | 0.8478 |
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+ | 0.2942 | 16.0 | 104 | 0.5791 | 0.8043 |
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+ | 0.2096 | 16.92 | 110 | 0.5814 | 0.7826 |
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+ | 0.2096 | 18.0 | 117 | 0.7829 | 0.7174 |
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+ | 0.2113 | 18.92 | 123 | 0.5658 | 0.8478 |
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+ | 0.2143 | 20.0 | 130 | 0.7036 | 0.7609 |
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+ | 0.2143 | 20.92 | 136 | 0.5924 | 0.7826 |
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+ | 0.1752 | 22.0 | 143 | 0.6852 | 0.7609 |
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+ | 0.1752 | 22.92 | 149 | 0.7237 | 0.7609 |
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+ | 0.1238 | 24.0 | 156 | 0.6743 | 0.8043 |
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+ | 0.1401 | 24.92 | 162 | 0.8463 | 0.6957 |
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+ | 0.1401 | 26.0 | 169 | 0.7872 | 0.7609 |
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+ | 0.1544 | 26.92 | 175 | 0.5492 | 0.8261 |
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+ | 0.1163 | 28.0 | 182 | 0.5756 | 0.8043 |
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+ | 0.1163 | 28.92 | 188 | 0.7621 | 0.7609 |
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+ | 0.1121 | 30.0 | 195 | 0.6972 | 0.7826 |
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+ | 0.1065 | 30.92 | 201 | 0.5723 | 0.8261 |
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+ | 0.1065 | 32.0 | 208 | 0.7503 | 0.8261 |
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+ | 0.1021 | 32.92 | 214 | 0.6127 | 0.8043 |
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+ | 0.1048 | 34.0 | 221 | 0.5734 | 0.8478 |
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+ | 0.1048 | 34.92 | 227 | 0.5817 | 0.8478 |
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+ | 0.0848 | 36.0 | 234 | 0.5903 | 0.8261 |
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+ | 0.0769 | 36.92 | 240 | 0.7074 | 0.8261 |
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+ | 0.0769 | 38.0 | 247 | 0.5835 | 0.8478 |
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+ | 0.0825 | 38.92 | 253 | 0.6373 | 0.8043 |
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+ | 0.0676 | 40.0 | 260 | 0.6793 | 0.8261 |
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+ | 0.0676 | 40.92 | 266 | 0.6556 | 0.8261 |
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+ | 0.0703 | 42.0 | 273 | 0.6329 | 0.8478 |
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+ | 0.0703 | 42.92 | 279 | 0.6868 | 0.8261 |
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+ | 0.0574 | 44.0 | 286 | 0.5997 | 0.8043 |
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+ | 0.0523 | 44.92 | 292 | 0.5846 | 0.8261 |
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+ | 0.0523 | 46.0 | 299 | 0.7214 | 0.8478 |
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+ | 0.064 | 46.92 | 305 | 0.5230 | 0.8478 |
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+ | 0.082 | 48.0 | 312 | 0.5850 | 0.8478 |
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+ | 0.082 | 48.92 | 318 | 0.6346 | 0.8478 |
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+ | 0.0694 | 50.0 | 325 | 0.6389 | 0.8261 |
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+ | 0.0462 | 50.92 | 331 | 0.5813 | 0.8478 |
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+ | 0.0462 | 52.0 | 338 | 0.5792 | 0.8478 |
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+ | 0.044 | 52.92 | 344 | 0.5724 | 0.8261 |
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+ | 0.0538 | 54.0 | 351 | 0.6294 | 0.8261 |
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+ | 0.0538 | 54.92 | 357 | 0.5742 | 0.8696 |
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+ | 0.0455 | 56.0 | 364 | 0.6951 | 0.8043 |
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+ | 0.0537 | 56.92 | 370 | 0.6458 | 0.8043 |
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+ | 0.0537 | 58.0 | 377 | 0.6259 | 0.8478 |
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+ | 0.038 | 58.92 | 383 | 0.6748 | 0.8478 |
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+ | 0.039 | 60.0 | 390 | 0.7236 | 0.8261 |
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+ | 0.039 | 60.92 | 396 | 0.7758 | 0.8261 |
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+ | 0.0304 | 62.0 | 403 | 0.7253 | 0.7609 |
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+ | 0.0304 | 62.92 | 409 | 0.7513 | 0.8261 |
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+ | 0.051 | 64.0 | 416 | 0.7547 | 0.8261 |
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+ | 0.0355 | 64.92 | 422 | 0.8115 | 0.7826 |
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+ | 0.0355 | 66.0 | 429 | 0.7768 | 0.8043 |
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+ | 0.0435 | 66.92 | 435 | 0.7829 | 0.8043 |
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+ | 0.0313 | 68.0 | 442 | 0.7787 | 0.8043 |
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+ | 0.0313 | 68.92 | 448 | 0.7721 | 0.8261 |
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+ | 0.0378 | 70.0 | 455 | 0.7672 | 0.8261 |
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+ | 0.0339 | 70.92 | 461 | 0.7634 | 0.8261 |
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+ | 0.0339 | 72.0 | 468 | 0.7615 | 0.8261 |
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+ | 0.0311 | 72.92 | 474 | 0.7605 | 0.8261 |
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+ | 0.0302 | 73.85 | 480 | 0.7603 | 0.8261 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.36.2
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+ - Pytorch 2.1.2+cu118
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+ - Datasets 2.16.1
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+ - Tokenizers 0.15.0
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