End of training

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: google/efficientnet-b0
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- precision
+- recall
+- f1
+model-index:
+- name: efficientnet-b0
+  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. -->
+
+# efficientnet-b0
+
+This model is a fine-tuned version of [google/efficientnet-b0](https://huggingface.co/google/efficientnet-b0) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0667
+- Accuracy: 0.9820
+- Precision: 0.9906
+- Recall: 0.9701
+- F1: 0.9803
+- Tp: 1589
+- Tn: 1895
+- Fp: 15
+- Fn: 49
+
+## 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: 0.0003
+- train_batch_size: 128
+- eval_batch_size: 128
+- 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: 55
+- num_epochs: 5
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Accuracy | Precision | Recall | F1     | Tp   | Tn   | Fp  | Fn  |
+|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:----:|:----:|:---:|:---:|
+| 0.6186        | 0.0991 | 11   | 0.5844          | 0.8554   | 0.8220    | 0.8767 | 0.8484 | 1436 | 1599 | 311 | 202 |
+| 0.4352        | 0.1982 | 22   | 0.3699          | 0.9109   | 0.9070    | 0.8993 | 0.9031 | 1473 | 1759 | 151 | 165 |
+| 0.3375        | 0.2973 | 33   | 0.2767          | 0.9270   | 0.9395    | 0.8999 | 0.9192 | 1474 | 1815 | 95  | 164 |
+| 0.2587        | 0.3964 | 44   | 0.3335          | 0.8636   | 0.7980    | 0.9432 | 0.8646 | 1545 | 1519 | 391 | 93  |
+| 0.2685        | 0.4955 | 55   | 0.2499          | 0.9039   | 0.8601    | 0.9457 | 0.9008 | 1549 | 1658 | 252 | 89  |
+| 0.2301        | 0.5946 | 66   | 0.2030          | 0.9493   | 0.9539    | 0.9353 | 0.9445 | 1532 | 1836 | 74  | 106 |
+| 0.2156        | 0.6937 | 77   | 0.2916          | 0.9132   | 0.8662    | 0.9603 | 0.9108 | 1573 | 1667 | 243 | 65  |
+| 0.2061        | 0.7928 | 88   | 0.1965          | 0.9501   | 0.9441    | 0.9481 | 0.9461 | 1553 | 1818 | 92  | 85  |
+| 0.2247        | 0.8919 | 99   | 0.3334          | 0.8963   | 0.8356    | 0.9652 | 0.8958 | 1581 | 1599 | 311 | 57  |
+| 0.2066        | 0.9910 | 110  | 0.1734          | 0.9580   | 0.9515    | 0.9579 | 0.9547 | 1569 | 1830 | 80  | 69  |
+| 0.1943        | 1.0901 | 121  | 0.1477          | 0.9665   | 0.9768    | 0.9499 | 0.9632 | 1556 | 1873 | 37  | 82  |
+| 0.1881        | 1.1892 | 132  | 0.2671          | 0.9343   | 0.9003    | 0.9646 | 0.9313 | 1580 | 1735 | 175 | 58  |
+| 0.1930        | 1.2883 | 143  | 0.1364          | 0.9701   | 0.9793    | 0.9554 | 0.9672 | 1565 | 1877 | 33  | 73  |
+| 0.1695        | 1.3874 | 154  | 0.5418          | 0.8802   | 0.8077    | 0.9719 | 0.8822 | 1592 | 1531 | 379 | 46  |
+| 0.1953        | 1.4865 | 165  | 0.2503          | 0.9366   | 0.9058    | 0.9628 | 0.9334 | 1577 | 1746 | 164 | 61  |
+| 0.1657        | 1.5856 | 176  | 0.2650          | 0.9183   | 0.8663    | 0.9731 | 0.9166 | 1594 | 1664 | 246 | 44  |
+| 0.1700        | 1.6847 | 187  | 0.1186          | 0.9679   | 0.9681    | 0.9621 | 0.9651 | 1576 | 1858 | 52  | 62  |
+| 0.1838        | 1.7838 | 198  | 0.3018          | 0.9166   | 0.8631    | 0.9737 | 0.9151 | 1595 | 1657 | 253 | 43  |
+| 0.1837        | 1.8829 | 209  | 0.1432          | 0.9549   | 0.9352    | 0.9695 | 0.9520 | 1588 | 1800 | 110 | 50  |
+| 0.1599        | 1.9820 | 220  | 0.1117          | 0.9625   | 0.9514    | 0.9683 | 0.9598 | 1586 | 1829 | 81  | 52  |
+| 0.1431        | 2.0811 | 231  | 0.0925          | 0.9710   | 0.9711    | 0.9658 | 0.9685 | 1582 | 1863 | 47  | 56  |
+| 0.1436        | 2.1802 | 242  | 0.1248          | 0.9628   | 0.9461    | 0.9750 | 0.9603 | 1597 | 1819 | 91  | 41  |
+| 0.1649        | 2.2793 | 253  | 0.1036          | 0.9713   | 0.9723    | 0.9652 | 0.9688 | 1581 | 1865 | 45  | 57  |
+| 0.1494        | 2.3784 | 264  | 0.1626          | 0.9521   | 0.9338    | 0.9646 | 0.9489 | 1580 | 1798 | 112 | 58  |
+| 0.1646        | 2.4775 | 275  | 0.1149          | 0.9710   | 0.9723    | 0.9646 | 0.9684 | 1580 | 1865 | 45  | 58  |
+| 0.1570        | 2.5766 | 286  | 0.0903          | 0.9811   | 0.9925    | 0.9664 | 0.9793 | 1583 | 1898 | 12  | 55  |
+| 0.1490        | 2.6757 | 297  | 0.0810          | 0.9794   | 0.9857    | 0.9695 | 0.9775 | 1588 | 1887 | 23  | 50  |
+| 0.1752        | 2.7748 | 308  | 0.3121          | 0.9185   | 0.8791    | 0.9548 | 0.9154 | 1564 | 1695 | 215 | 74  |
+| 0.1384        | 2.8739 | 319  | 0.1137          | 0.9710   | 0.9626    | 0.9750 | 0.9688 | 1597 | 1848 | 62  | 41  |
+| 0.1629        | 2.9730 | 330  | 0.0993          | 0.9746   | 0.9748    | 0.9701 | 0.9725 | 1589 | 1869 | 41  | 49  |
+| 0.1435        | 3.0721 | 341  | 0.0854          | 0.9791   | 0.9821    | 0.9725 | 0.9773 | 1593 | 1881 | 29  | 45  |
+| 0.1652        | 3.1712 | 352  | 0.1394          | 0.9605   | 0.9448    | 0.9713 | 0.9579 | 1591 | 1817 | 93  | 47  |
+| 0.1622        | 3.2703 | 363  | 0.1351          | 0.9636   | 0.9494    | 0.9731 | 0.9611 | 1594 | 1825 | 85  | 44  |
+| 0.1506        | 3.3694 | 374  | 0.0782          | 0.9817   | 0.9846    | 0.9756 | 0.9801 | 1598 | 1885 | 25  | 40  |
+| 0.1417        | 3.4685 | 385  | 0.0694          | 0.9828   | 0.9907    | 0.9719 | 0.9812 | 1592 | 1895 | 15  | 46  |
+| 0.1311        | 3.5676 | 396  | 0.0779          | 0.9786   | 0.9803    | 0.9731 | 0.9767 | 1594 | 1878 | 32  | 44  |
+| 0.1353        | 3.6667 | 407  | 0.0670          | 0.9817   | 0.9906    | 0.9695 | 0.9799 | 1588 | 1895 | 15  | 50  |
+| 0.1566        | 3.7658 | 418  | 0.0856          | 0.9780   | 0.9821    | 0.9701 | 0.9760 | 1589 | 1881 | 29  | 49  |
+| 0.1309        | 3.8649 | 429  | 0.0800          | 0.9794   | 0.9833    | 0.9719 | 0.9776 | 1592 | 1883 | 27  | 46  |
+| 0.1524        | 3.9640 | 440  | 0.1037          | 0.9741   | 0.9713    | 0.9725 | 0.9719 | 1593 | 1863 | 47  | 45  |
+| 0.1531        | 4.0631 | 451  | 0.1045          | 0.9724   | 0.9684    | 0.9719 | 0.9701 | 1592 | 1858 | 52  | 46  |
+| 0.1517        | 4.1622 | 462  | 0.1169          | 0.9653   | 0.9544    | 0.9713 | 0.9628 | 1591 | 1834 | 76  | 47  |
+| 0.1645        | 4.2613 | 473  | 0.1061          | 0.9698   | 0.9598    | 0.9756 | 0.9676 | 1598 | 1843 | 67  | 40  |
+| 0.1177        | 4.3604 | 484  | 0.0710          | 0.9808   | 0.9894    | 0.9689 | 0.9790 | 1587 | 1893 | 17  | 51  |
+| 0.1419        | 4.4595 | 495  | 0.1014          | 0.9738   | 0.9685    | 0.9750 | 0.9717 | 1597 | 1858 | 52  | 41  |
+| 0.1356        | 4.5586 | 506  | 0.0646          | 0.9848   | 0.995     | 0.9719 | 0.9833 | 1592 | 1902 | 8   | 46  |
+| 0.1673        | 4.6577 | 517  | 0.1119          | 0.9713   | 0.9632    | 0.9750 | 0.9691 | 1597 | 1849 | 61  | 41  |
+| 0.1297        | 4.7568 | 528  | 0.0836          | 0.9780   | 0.9797    | 0.9725 | 0.9761 | 1593 | 1877 | 33  | 45  |
+| 0.1486        | 4.8559 | 539  | 0.0920          | 0.9772   | 0.9761    | 0.9744 | 0.9753 | 1596 | 1871 | 39  | 42  |
+| 0.1393        | 4.9550 | 550  | 0.0667          | 0.9820   | 0.9906    | 0.9701 | 0.9803 | 1589 | 1895 | 15  | 49  |
+
+
+### Framework versions
+
+- Transformers 5.2.0
+- Pytorch 2.9.0+cu126
+- Datasets 4.0.0
+- Tokenizers 0.22.2

config.json

@@ -0,0 +1,99 @@
+{
+  "architectures": [
+    "EfficientNetForImageClassification"
+  ],
+  "batch_norm_eps": 0.001,
+  "batch_norm_momentum": 0.99,
+  "depth_coefficient": 1.0,
+  "depth_divisor": 8,
+  "depthwise_padding": [],
+  "drop_connect_rate": 0.2,
+  "dropout_rate": 0.2,
+  "dtype": "float32",
+  "expand_ratios": [
+    1,
+    6,
+    6,
+    6,
+    6,
+    6,
+    6
+  ],
+  "hidden_act": "swish",
+  "hidden_dim": 1280,
+  "id2label": {
+    "0": "0",
+    "1": "1"
+  },
+  "image_size": 224,
+  "in_channels": [
+    32,
+    16,
+    24,
+    40,
+    80,
+    112,
+    192
+  ],
+  "initializer_range": 0.02,
+  "kernel_sizes": [
+    3,
+    3,
+    5,
+    3,
+    5,
+    5,
+    3
+  ],
+  "label2id": {
+    "0": 0,
+    "1": 1
+  },
+  "model_type": "efficientnet",
+  "num_block_repeats": [
+    1,
+    2,
+    2,
+    3,
+    3,
+    4,
+    1
+  ],
+  "num_channels": 3,
+  "num_hidden_layers": 64,
+  "out_channels": [
+    16,
+    24,
+    40,
+    80,
+    112,
+    192,
+    320
+  ],
+  "out_features": null,
+  "pooling_type": "mean",
+  "problem_type": "single_label_classification",
+  "squeeze_expansion_ratio": 0.25,
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4",
+    "stage5",
+    "stage6",
+    "stage7"
+  ],
+  "strides": [
+    1,
+    2,
+    2,
+    2,
+    1,
+    2,
+    1
+  ],
+  "transformers_version": "5.2.0",
+  "use_cache": false,
+  "width_coefficient": 1.0
+}

model.safetensors

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+oid sha256:142f3c8f1efdc4e2d87fa98f61f30e00515c414bfec123e37f7ea82f51ef88ec
+size 16255128

preprocessor_config.json

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+{
+  "crop_size": {
+    "height": 289,
+    "width": 289
+  },
+  "data_format": "channels_first",
+  "do_center_crop": false,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "EfficientNetImageProcessorFast",
+  "image_std": [
+    0.47853944,
+    0.4732864,
+    0.47434163
+  ],
+  "include_top": true,
+  "resample": 0,
+  "rescale_factor": 0.00392156862745098,
+  "rescale_offset": false,
+  "size": {
+    "height": 224,
+    "width": 224
+  }
+}

training_args.bin

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+oid sha256:daa722f63e02659ccb4cec536e21485800eae768d6cb31bfdf17886d57977d73
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