End of training

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: timm/tf_efficientnetv2_s.in21k
+tags:
+- timm
+- generated_from_trainer
+metrics:
+- accuracy
+- precision
+- recall
+- f1
+model-index:
+- name: EfficientNetV2_Small_v1
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# EfficientNetV2_Small_v1
+
+This model is a fine-tuned version of [timm/tf_efficientnetv2_s.in21k](https://huggingface.co/timm/tf_efficientnetv2_s.in21k) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0340
+- Accuracy: 0.9935
+- Precision: 0.9981
+- Recall: 0.9878
+- F1: 0.9929
+- Tp: 1618
+- Tn: 1907
+- Fp: 3
+- Fn: 20
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 0.0001
+- train_batch_size: 64
+- eval_batch_size: 64
+- seed: 42
+- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 442
+- num_epochs: 20
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     | Tp   | Tn   | Fp | Fn |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:----:|:----:|:--:|:--:|
+| 0.1995        | 1.0   | 222  | 0.1349          | 0.9628   | 0.9575    | 0.9621 | 0.9598 | 1576 | 1840 | 70 | 62 |
+| 0.1442        | 2.0   | 444  | 0.0940          | 0.9789   | 0.9956    | 0.9585 | 0.9767 | 1570 | 1903 | 7  | 68 |
+| 0.1625        | 3.0   | 666  | 0.0827          | 0.9837   | 0.9925    | 0.9719 | 0.9821 | 1592 | 1898 | 12 | 46 |
+| 0.1592        | 4.0   | 888  | 0.0926          | 0.9752   | 0.9708    | 0.9756 | 0.9732 | 1598 | 1862 | 48 | 40 |
+| 0.1100        | 5.0   | 1110 | 0.0544          | 0.9876   | 0.9950    | 0.9780 | 0.9865 | 1602 | 1902 | 8  | 36 |
+| 0.1497        | 6.0   | 1332 | 0.0635          | 0.9868   | 0.9877    | 0.9835 | 0.9856 | 1611 | 1890 | 20 | 27 |
+| 0.1125        | 7.0   | 1554 | 0.0485          | 0.9896   | 0.9957    | 0.9817 | 0.9886 | 1608 | 1903 | 7  | 30 |
+| 0.1202        | 8.0   | 1776 | 0.0774          | 0.9794   | 0.9740    | 0.9817 | 0.9778 | 1608 | 1867 | 43 | 30 |
+| 0.1031        | 9.0   | 1998 | 0.0507          | 0.9893   | 0.9938    | 0.9829 | 0.9883 | 1610 | 1900 | 10 | 28 |
+| 0.1211        | 10.0  | 2220 | 0.0434          | 0.9915   | 0.9975    | 0.9841 | 0.9908 | 1612 | 1906 | 4  | 26 |
+| 0.1239        | 11.0  | 2442 | 0.0400          | 0.9918   | 0.9975    | 0.9847 | 0.9911 | 1613 | 1906 | 4  | 25 |
+| 0.1066        | 12.0  | 2664 | 0.0403          | 0.9927   | 0.9988    | 0.9853 | 0.9920 | 1614 | 1908 | 2  | 24 |
+| 0.1065        | 13.0  | 2886 | 0.0363          | 0.9927   | 0.9994    | 0.9847 | 0.9920 | 1613 | 1909 | 1  | 25 |
+| 0.1074        | 14.0  | 3108 | 0.0378          | 0.9930   | 0.9988    | 0.9860 | 0.9923 | 1615 | 1908 | 2  | 23 |
+| 0.1128        | 15.0  | 3330 | 0.0327          | 0.9924   | 0.9981    | 0.9853 | 0.9917 | 1614 | 1907 | 3  | 24 |
+| 0.0963        | 16.0  | 3552 | 0.0309          | 0.9930   | 0.9988    | 0.9860 | 0.9923 | 1615 | 1908 | 2  | 23 |
+| 0.1379        | 17.0  | 3774 | 0.0366          | 0.9927   | 0.9969    | 0.9872 | 0.9920 | 1617 | 1905 | 5  | 21 |
+| 0.1070        | 18.0  | 3996 | 0.0331          | 0.9930   | 0.9981    | 0.9866 | 0.9923 | 1616 | 1907 | 3  | 22 |
+| 0.1332        | 19.0  | 4218 | 0.0343          | 0.9930   | 0.9981    | 0.9866 | 0.9923 | 1616 | 1907 | 3  | 22 |
+| 0.1294        | 20.0  | 4440 | 0.0340          | 0.9935   | 0.9981    | 0.9878 | 0.9929 | 1618 | 1907 | 3  | 20 |
+
+
+### Framework versions
+
+- Transformers 5.2.0
+- Pytorch 2.9.0+cu126
+- Datasets 4.0.0
+- Tokenizers 0.22.2

config.json

@@ -0,0 +1,54 @@
+{
+  "architecture": "tf_efficientnetv2_s",
+  "architectures": [
+    "TimmWrapperForImageClassification"
+  ],
+  "do_pooling": true,
+  "dtype": "float32",
+  "initializer_range": 0.02,
+  "label_names": [
+    "0",
+    "1"
+  ],
+  "model_args": null,
+  "model_type": "timm_wrapper",
+  "num_classes": 2,
+  "num_features": 1280,
+  "pretrained_cfg": {
+    "classifier": "classifier",
+    "crop_mode": "center",
+    "crop_pct": 1.0,
+    "custom_load": false,
+    "first_conv": "conv_stem",
+    "fixed_input_size": false,
+    "input_size": [
+      3,
+      300,
+      300
+    ],
+    "interpolation": "bicubic",
+    "mean": [
+      0.5,
+      0.5,
+      0.5
+    ],
+    "pool_size": [
+      10,
+      10
+    ],
+    "std": [
+      0.5,
+      0.5,
+      0.5
+    ],
+    "tag": "in21k",
+    "test_input_size": [
+      3,
+      384,
+      384
+    ]
+  },
+  "problem_type": "single_label_classification",
+  "transformers_version": "5.2.0",
+  "use_cache": false
+}

model.safetensors

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training_args.bin

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