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font-identifier

Image Classification
Transformers
Safetensors
resnet
Generated from Trainer
Eval Results (legacy)
Model card Files
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README.md ADDED
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+ ---
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+ library_name: transformers
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+ license: apache-2.0
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+ base_model: microsoft/resnet-18
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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: font-identifier
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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: 0.9545454545454546
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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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+ # font-identifier
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+
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+ This model is a fine-tuned version of [microsoft/resnet-18](https://huggingface.co/microsoft/resnet-18) on the imagefolder dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.1433
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+ - Accuracy: 0.9545
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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: 16
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+ - eval_batch_size: 16
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+ - seed: 42
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+ - gradient_accumulation_steps: 4
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+ - total_train_batch_size: 64
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+ - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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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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+ | 3.3794 | 1.0 | 14 | 3.3306 | 0.0455 |
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+ | 3.1945 | 2.0 | 28 | 3.0211 | 0.1045 |
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+ | 2.9016 | 3.0 | 42 | 2.6297 | 0.1682 |
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+ | 2.5174 | 4.0 | 56 | 2.1280 | 0.3636 |
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+ | 1.8477 | 5.0 | 70 | 1.6542 | 0.5318 |
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+ | 1.6209 | 6.0 | 84 | 1.2193 | 0.6136 |
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+ | 1.3882 | 7.0 | 98 | 1.0877 | 0.6636 |
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+ | 1.1235 | 8.0 | 112 | 0.8903 | 0.7318 |
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+ | 1.0144 | 9.0 | 126 | 0.7754 | 0.7818 |
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+ | 0.7593 | 10.0 | 140 | 0.6333 | 0.8 |
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+ | 0.801 | 11.0 | 154 | 0.5506 | 0.8091 |
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+ | 0.745 | 12.0 | 168 | 0.4354 | 0.8636 |
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+ | 0.5987 | 13.0 | 182 | 0.4478 | 0.8636 |
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+ | 0.5947 | 14.0 | 196 | 0.4014 | 0.8682 |
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+ | 0.4595 | 15.0 | 210 | 0.4270 | 0.8591 |
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+ | 0.5095 | 16.0 | 224 | 0.2876 | 0.9227 |
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+ | 0.4554 | 17.0 | 238 | 0.3371 | 0.8727 |
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+ | 0.3733 | 18.0 | 252 | 0.2550 | 0.9227 |
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+ | 0.3888 | 19.0 | 266 | 0.3142 | 0.8818 |
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+ | 0.4014 | 20.0 | 280 | 0.2550 | 0.9273 |
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+ | 0.3493 | 21.0 | 294 | 0.2737 | 0.9091 |
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+ | 0.3637 | 22.0 | 308 | 0.2399 | 0.9091 |
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+ | 0.3479 | 23.0 | 322 | 0.1852 | 0.9455 |
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+ | 0.3303 | 24.0 | 336 | 0.2029 | 0.9364 |
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+ | 0.3147 | 25.0 | 350 | 0.2294 | 0.9318 |
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+ | 0.2976 | 26.0 | 364 | 0.2396 | 0.9091 |
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+ | 0.2937 | 27.0 | 378 | 0.2169 | 0.9455 |
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+ | 0.2597 | 28.0 | 392 | 0.1885 | 0.9227 |
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+ | 0.2685 | 29.0 | 406 | 0.1743 | 0.9545 |
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+ | 0.2465 | 30.0 | 420 | 0.1985 | 0.9318 |
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+ | 0.2753 | 31.0 | 434 | 0.1814 | 0.9364 |
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+ | 0.224 | 32.0 | 448 | 0.1823 | 0.9182 |
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+ | 0.2324 | 33.0 | 462 | 0.1634 | 0.9318 |
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+ | 0.2163 | 34.0 | 476 | 0.1686 | 0.9364 |
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+ | 0.2116 | 35.0 | 490 | 0.1502 | 0.9682 |
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+ | 0.2511 | 36.0 | 504 | 0.1817 | 0.9364 |
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+ | 0.238 | 37.0 | 518 | 0.1489 | 0.9318 |
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+ | 0.2187 | 38.0 | 532 | 0.1455 | 0.9364 |
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+ | 0.1822 | 39.0 | 546 | 0.1260 | 0.9591 |
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+ | 0.1799 | 40.0 | 560 | 0.1632 | 0.95 |
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+ | 0.2013 | 41.0 | 574 | 0.1442 | 0.9545 |
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+ | 0.2065 | 42.0 | 588 | 0.1709 | 0.9409 |
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+ | 0.2244 | 43.0 | 602 | 0.1692 | 0.9591 |
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+ | 0.1965 | 44.0 | 616 | 0.1326 | 0.95 |
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+ | 0.1694 | 45.0 | 630 | 0.1666 | 0.95 |
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+ | 0.1755 | 46.0 | 644 | 0.1189 | 0.9591 |
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+ | 0.1939 | 47.0 | 658 | 0.1444 | 0.95 |
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+ | 0.192 | 48.0 | 672 | 0.1828 | 0.9364 |
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+ | 0.178 | 49.0 | 686 | 0.1806 | 0.9273 |
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+ | 0.1742 | 50.0 | 700 | 0.1433 | 0.9545 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.53.3
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+ - Pytorch 2.2.2
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+ - Datasets 2.19.2
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+ - Tokenizers 0.21.2
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