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vit-base-patch16-224-ve-U11-b-80

Image Classification
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vit
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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-U11-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: 0.8043478260869565
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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-U11-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: 0.8161
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+ - Accuracy: 0.8043
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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 | 0.3696 |
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+ | 1.3848 | 2.0 | 13 | 1.3692 | 0.5217 |
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+ | 1.3848 | 2.92 | 19 | 1.3197 | 0.5435 |
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+ | 1.3517 | 4.0 | 26 | 1.2264 | 0.5 |
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+ | 1.2334 | 4.92 | 32 | 1.1280 | 0.4348 |
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+ | 1.2334 | 6.0 | 39 | 1.0437 | 0.5435 |
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+ | 1.073 | 6.92 | 45 | 0.9771 | 0.5870 |
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+ | 0.9358 | 8.0 | 52 | 0.9470 | 0.6739 |
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+ | 0.9358 | 8.92 | 58 | 0.8528 | 0.7826 |
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+ | 0.7955 | 10.0 | 65 | 0.7839 | 0.7609 |
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+ | 0.6429 | 10.92 | 71 | 0.7620 | 0.7391 |
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+ | 0.6429 | 12.0 | 78 | 0.6466 | 0.8043 |
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+ | 0.5096 | 12.92 | 84 | 0.7396 | 0.7174 |
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+ | 0.4086 | 14.0 | 91 | 0.7335 | 0.7174 |
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+ | 0.4086 | 14.92 | 97 | 0.6473 | 0.7391 |
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+ | 0.3355 | 16.0 | 104 | 0.6019 | 0.7391 |
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+ | 0.2511 | 16.92 | 110 | 0.5275 | 0.8261 |
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+ | 0.2511 | 18.0 | 117 | 0.6069 | 0.7826 |
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+ | 0.1925 | 18.92 | 123 | 0.6447 | 0.7826 |
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+ | 0.2121 | 20.0 | 130 | 0.5044 | 0.8261 |
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+ | 0.2121 | 20.92 | 136 | 0.4805 | 0.8478 |
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+ | 0.1883 | 22.0 | 143 | 0.6723 | 0.8043 |
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+ | 0.1883 | 22.92 | 149 | 0.7730 | 0.7391 |
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+ | 0.1693 | 24.0 | 156 | 0.6574 | 0.7609 |
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+ | 0.1252 | 24.92 | 162 | 0.8192 | 0.7391 |
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+ | 0.1252 | 26.0 | 169 | 0.5984 | 0.7826 |
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+ | 0.1439 | 26.92 | 175 | 0.7633 | 0.7826 |
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+ | 0.137 | 28.0 | 182 | 0.6566 | 0.8478 |
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+ | 0.137 | 28.92 | 188 | 0.6550 | 0.8261 |
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+ | 0.1316 | 30.0 | 195 | 0.7163 | 0.7391 |
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+ | 0.1101 | 30.92 | 201 | 0.6241 | 0.7826 |
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+ | 0.1101 | 32.0 | 208 | 0.6360 | 0.8478 |
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+ | 0.0947 | 32.92 | 214 | 0.5273 | 0.8696 |
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+ | 0.0885 | 34.0 | 221 | 0.6579 | 0.8261 |
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+ | 0.0885 | 34.92 | 227 | 0.5920 | 0.8696 |
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+ | 0.0967 | 36.0 | 234 | 0.6779 | 0.8261 |
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+ | 0.0812 | 36.92 | 240 | 0.7354 | 0.8043 |
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+ | 0.0812 | 38.0 | 247 | 0.6825 | 0.8261 |
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+ | 0.0752 | 38.92 | 253 | 0.6348 | 0.8478 |
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+ | 0.0757 | 40.0 | 260 | 0.7726 | 0.8043 |
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+ | 0.0757 | 40.92 | 266 | 0.6737 | 0.8261 |
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+ | 0.086 | 42.0 | 273 | 0.6738 | 0.7826 |
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+ | 0.086 | 42.92 | 279 | 0.7295 | 0.7609 |
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+ | 0.0533 | 44.0 | 286 | 0.6897 | 0.8261 |
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+ | 0.0574 | 44.92 | 292 | 0.6427 | 0.8261 |
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+ | 0.0574 | 46.0 | 299 | 0.6471 | 0.8261 |
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+ | 0.0739 | 46.92 | 305 | 0.6645 | 0.8261 |
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+ | 0.0849 | 48.0 | 312 | 0.6858 | 0.8043 |
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+ | 0.0849 | 48.92 | 318 | 0.7475 | 0.8043 |
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+ | 0.0719 | 50.0 | 325 | 0.6735 | 0.8261 |
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+ | 0.0434 | 50.92 | 331 | 0.6892 | 0.8478 |
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+ | 0.0434 | 52.0 | 338 | 0.6820 | 0.8478 |
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+ | 0.0564 | 52.92 | 344 | 0.6677 | 0.8478 |
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+ | 0.0408 | 54.0 | 351 | 0.7379 | 0.8043 |
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+ | 0.0408 | 54.92 | 357 | 0.5456 | 0.8913 |
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+ | 0.0464 | 56.0 | 364 | 0.7951 | 0.7826 |
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+ | 0.0463 | 56.92 | 370 | 0.6356 | 0.8478 |
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+ | 0.0463 | 58.0 | 377 | 0.7529 | 0.8261 |
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+ | 0.0361 | 58.92 | 383 | 0.8017 | 0.8261 |
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+ | 0.0457 | 60.0 | 390 | 0.7877 | 0.8478 |
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+ | 0.0457 | 60.92 | 396 | 0.8019 | 0.7826 |
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+ | 0.0371 | 62.0 | 403 | 0.8015 | 0.8043 |
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+ | 0.0371 | 62.92 | 409 | 0.8487 | 0.8043 |
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+ | 0.0452 | 64.0 | 416 | 0.9401 | 0.7609 |
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+ | 0.0455 | 64.92 | 422 | 0.9647 | 0.7609 |
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+ | 0.0455 | 66.0 | 429 | 0.8958 | 0.7609 |
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+ | 0.0408 | 66.92 | 435 | 0.8531 | 0.7826 |
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+ | 0.0418 | 68.0 | 442 | 0.8206 | 0.8043 |
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+ | 0.0418 | 68.92 | 448 | 0.8045 | 0.8043 |
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+ | 0.0424 | 70.0 | 455 | 0.8090 | 0.8043 |
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+ | 0.038 | 70.92 | 461 | 0.7902 | 0.8043 |
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+ | 0.038 | 72.0 | 468 | 0.8008 | 0.8261 |
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+ | 0.0401 | 72.92 | 474 | 0.8122 | 0.8043 |
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+ | 0.0347 | 73.85 | 480 | 0.8161 | 0.8043 |
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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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