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

Image Classification
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  2. model.safetensors +1 -1
  3. runs/Jun12_14-27-46_DESKTOP-SKBE9FB/events.out.tfevents.1718224067.DESKTOP-SKBE9FB.14480.0 +2 -2
README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: microsoft/beit-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: beit-base-patch16-224-ve-U13-b-80b
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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: 0.782608695652174
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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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+ # beit-base-patch16-224-ve-U13-b-80b
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+
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+ This model is a fine-tuned version of [microsoft/beit-base-patch16-224](https://huggingface.co/microsoft/beit-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: 0.9549
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+ - Accuracy: 0.7826
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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: 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: 0.1
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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 | 1.3182 | 0.4565 |
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+ | 1.6182 | 2.0 | 13 | 1.3056 | 0.4565 |
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+ | 1.6182 | 2.92 | 19 | 1.2884 | 0.4565 |
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+ | 1.592 | 4.0 | 26 | 1.2807 | 0.4565 |
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+ | 1.4756 | 4.92 | 32 | 1.2991 | 0.4565 |
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+ | 1.4756 | 6.0 | 39 | 1.2451 | 0.5 |
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+ | 1.352 | 6.92 | 45 | 1.1845 | 0.5217 |
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+ | 1.2143 | 8.0 | 52 | 1.0315 | 0.6087 |
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+ | 1.2143 | 8.92 | 58 | 0.9289 | 0.5435 |
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+ | 1.0327 | 10.0 | 65 | 0.8925 | 0.5435 |
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+ | 0.8878 | 10.92 | 71 | 0.8633 | 0.5652 |
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+ | 0.8878 | 12.0 | 78 | 0.7566 | 0.6304 |
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+ | 0.7712 | 12.92 | 84 | 0.7669 | 0.7609 |
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+ | 0.6808 | 14.0 | 91 | 0.7635 | 0.7609 |
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+ | 0.6808 | 14.92 | 97 | 0.8653 | 0.6304 |
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+ | 0.5844 | 16.0 | 104 | 0.7193 | 0.7174 |
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+ | 0.4332 | 16.92 | 110 | 0.6186 | 0.7826 |
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+ | 0.4332 | 18.0 | 117 | 1.0295 | 0.6739 |
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+ | 0.3607 | 18.92 | 123 | 0.8007 | 0.7609 |
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+ | 0.3134 | 20.0 | 130 | 0.6790 | 0.7826 |
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+ | 0.3134 | 20.92 | 136 | 0.8013 | 0.7391 |
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+ | 0.2988 | 22.0 | 143 | 0.7481 | 0.7609 |
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+ | 0.2988 | 22.92 | 149 | 0.9280 | 0.6739 |
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+ | 0.2487 | 24.0 | 156 | 0.6542 | 0.7391 |
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+ | 0.1912 | 24.92 | 162 | 0.7134 | 0.7609 |
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+ | 0.1912 | 26.0 | 169 | 0.8421 | 0.7609 |
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+ | 0.1946 | 26.92 | 175 | 0.7284 | 0.7391 |
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+ | 0.1685 | 28.0 | 182 | 0.7507 | 0.8261 |
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+ | 0.1685 | 28.92 | 188 | 0.7610 | 0.8043 |
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+ | 0.1646 | 30.0 | 195 | 0.8013 | 0.7826 |
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+ | 0.166 | 30.92 | 201 | 0.8803 | 0.7826 |
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+ | 0.166 | 32.0 | 208 | 0.7895 | 0.7391 |
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+ | 0.1372 | 32.92 | 214 | 0.7760 | 0.7174 |
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+ | 0.1424 | 34.0 | 221 | 0.9390 | 0.7174 |
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+ | 0.1424 | 34.92 | 227 | 0.7839 | 0.8043 |
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+ | 0.1399 | 36.0 | 234 | 0.9422 | 0.7609 |
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+ | 0.1238 | 36.92 | 240 | 0.8710 | 0.7174 |
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+ | 0.1238 | 38.0 | 247 | 0.8684 | 0.7826 |
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+ | 0.123 | 38.92 | 253 | 0.8194 | 0.7609 |
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+ | 0.1381 | 40.0 | 260 | 0.9698 | 0.7391 |
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+ | 0.1381 | 40.92 | 266 | 0.8545 | 0.7609 |
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+ | 0.1081 | 42.0 | 273 | 0.9925 | 0.6739 |
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+ | 0.1081 | 42.92 | 279 | 0.9320 | 0.8043 |
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+ | 0.0929 | 44.0 | 286 | 1.0242 | 0.7609 |
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+ | 0.0898 | 44.92 | 292 | 0.9411 | 0.7609 |
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+ | 0.0898 | 46.0 | 299 | 0.8995 | 0.7609 |
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+ | 0.12 | 46.92 | 305 | 0.7741 | 0.7826 |
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+ | 0.1126 | 48.0 | 312 | 0.7122 | 0.8478 |
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+ | 0.1126 | 48.92 | 318 | 0.9099 | 0.7826 |
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+ | 0.1088 | 50.0 | 325 | 1.1148 | 0.6957 |
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+ | 0.0851 | 50.92 | 331 | 0.9297 | 0.8043 |
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+ | 0.0851 | 52.0 | 338 | 0.8801 | 0.8043 |
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+ | 0.1001 | 52.92 | 344 | 0.8428 | 0.8261 |
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+ | 0.0718 | 54.0 | 351 | 0.9721 | 0.7826 |
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+ | 0.0718 | 54.92 | 357 | 0.8771 | 0.8043 |
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+ | 0.0842 | 56.0 | 364 | 0.9982 | 0.7826 |
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+ | 0.1069 | 56.92 | 370 | 1.1083 | 0.7391 |
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+ | 0.1069 | 58.0 | 377 | 0.9072 | 0.7826 |
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+ | 0.0803 | 58.92 | 383 | 0.7979 | 0.8261 |
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+ | 0.0752 | 60.0 | 390 | 0.7489 | 0.8478 |
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+ | 0.0752 | 60.92 | 396 | 0.8023 | 0.8261 |
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+ | 0.0646 | 62.0 | 403 | 0.8027 | 0.8261 |
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+ | 0.0646 | 62.92 | 409 | 0.8275 | 0.7826 |
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+ | 0.0829 | 64.0 | 416 | 0.8587 | 0.8043 |
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+ | 0.0616 | 64.92 | 422 | 0.8870 | 0.8043 |
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+ | 0.0616 | 66.0 | 429 | 0.8928 | 0.8043 |
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+ | 0.0693 | 66.92 | 435 | 0.9289 | 0.7826 |
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+ | 0.0657 | 68.0 | 442 | 0.9604 | 0.7609 |
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+ | 0.0657 | 68.92 | 448 | 0.9560 | 0.7826 |
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+ | 0.0588 | 70.0 | 455 | 0.9544 | 0.7609 |
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+ | 0.0578 | 70.92 | 461 | 0.9419 | 0.7826 |
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+ | 0.0578 | 72.0 | 468 | 0.9474 | 0.7826 |
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+ | 0.0638 | 72.92 | 474 | 0.9540 | 0.7826 |
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+ | 0.0592 | 73.85 | 480 | 0.9549 | 0.7826 |
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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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