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convnext-tiny-224-finetuned-papsmear

Image Classification
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convnext
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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: facebook/convnext-tiny-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: convnext-tiny-224-finetuned-papsmear
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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: train
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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: 0.8897058823529411
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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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+ # convnext-tiny-224-finetuned-papsmear
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+
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+ This model is a fine-tuned version of [facebook/convnext-tiny-224](https://huggingface.co/facebook/convnext-tiny-224) on the imagefolder dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.2738
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+ - Accuracy: 0.8897
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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: 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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+ | No log | 0.9231 | 9 | 1.7808 | 0.1691 |
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+ | 1.8057 | 1.9487 | 19 | 1.6808 | 0.3309 |
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+ | 1.7394 | 2.9744 | 29 | 1.5825 | 0.3382 |
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+ | 1.6408 | 4.0 | 39 | 1.4576 | 0.375 |
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+ | 1.5428 | 4.9231 | 48 | 1.3281 | 0.5221 |
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+ | 1.3931 | 5.9487 | 58 | 1.2044 | 0.5588 |
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+ | 1.2669 | 6.9744 | 68 | 1.0756 | 0.6103 |
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+ | 1.1355 | 8.0 | 78 | 0.9845 | 0.6324 |
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+ | 1.0379 | 8.9231 | 87 | 0.9260 | 0.6618 |
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+ | 0.9571 | 9.9487 | 97 | 0.8539 | 0.6618 |
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+ | 0.8376 | 10.9744 | 107 | 0.7998 | 0.7279 |
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+ | 0.7942 | 12.0 | 117 | 0.7573 | 0.75 |
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+ | 0.7095 | 12.9231 | 126 | 0.7005 | 0.7426 |
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+ | 0.7022 | 13.9487 | 136 | 0.6834 | 0.7868 |
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+ | 0.6504 | 14.9744 | 146 | 0.6552 | 0.7721 |
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+ | 0.589 | 16.0 | 156 | 0.6192 | 0.8015 |
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+ | 0.5679 | 16.9231 | 165 | 0.5738 | 0.8088 |
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+ | 0.5236 | 17.9487 | 175 | 0.5617 | 0.8015 |
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+ | 0.5244 | 18.9744 | 185 | 0.5073 | 0.8235 |
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+ | 0.4781 | 20.0 | 195 | 0.5112 | 0.8162 |
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+ | 0.453 | 20.9231 | 204 | 0.4650 | 0.8235 |
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+ | 0.4544 | 21.9487 | 214 | 0.4591 | 0.8456 |
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+ | 0.419 | 22.9744 | 224 | 0.4403 | 0.8309 |
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+ | 0.4146 | 24.0 | 234 | 0.4292 | 0.8382 |
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+ | 0.398 | 24.9231 | 243 | 0.4315 | 0.8382 |
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+ | 0.3918 | 25.9487 | 253 | 0.3980 | 0.8676 |
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+ | 0.361 | 26.9744 | 263 | 0.3758 | 0.8603 |
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+ | 0.3355 | 28.0 | 273 | 0.3657 | 0.8603 |
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+ | 0.3483 | 28.9231 | 282 | 0.3669 | 0.875 |
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+ | 0.3171 | 29.9487 | 292 | 0.3492 | 0.8603 |
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+ | 0.3249 | 30.9744 | 302 | 0.3400 | 0.875 |
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+ | 0.3087 | 32.0 | 312 | 0.3251 | 0.875 |
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+ | 0.3029 | 32.9231 | 321 | 0.3167 | 0.8824 |
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+ | 0.3018 | 33.9487 | 331 | 0.3192 | 0.875 |
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+ | 0.2823 | 34.9744 | 341 | 0.3066 | 0.875 |
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+ | 0.2744 | 36.0 | 351 | 0.3003 | 0.875 |
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+ | 0.258 | 36.9231 | 360 | 0.2964 | 0.875 |
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+ | 0.2714 | 37.9487 | 370 | 0.3039 | 0.875 |
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+ | 0.2486 | 38.9744 | 380 | 0.2937 | 0.875 |
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+ | 0.2511 | 40.0 | 390 | 0.2739 | 0.8824 |
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+ | 0.2511 | 40.9231 | 399 | 0.2836 | 0.8897 |
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+ | 0.2659 | 41.9487 | 409 | 0.2804 | 0.875 |
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+ | 0.2379 | 42.9744 | 419 | 0.2747 | 0.8824 |
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+ | 0.2279 | 44.0 | 429 | 0.2726 | 0.8897 |
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+ | 0.2153 | 44.9231 | 438 | 0.2732 | 0.8897 |
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+ | 0.2461 | 45.9487 | 448 | 0.2738 | 0.8897 |
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+ | 0.2482 | 46.1538 | 450 | 0.2738 | 0.8897 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.44.2
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+ - Pytorch 2.4.1+cu121
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+ - Datasets 3.0.1
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+ - Tokenizers 0.19.1
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