End of training

README.md

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+---
+library_name: transformers
+license: other
+base_model: google/mobilenet_v2_1.0_224
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- precision
+- recall
+- f1
+model-index:
+- name: ViT_L16
+  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. -->
+
+# ViT_L16
+
+This model is a fine-tuned version of [google/mobilenet_v2_1.0_224](https://huggingface.co/google/mobilenet_v2_1.0_224) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3409
+- Accuracy: 0.8904
+- Precision: 0.8746
+- Recall: 0.8901
+- F1: 0.8823
+- Tp: 1458
+- Tn: 1701
+- Fp: 209
+- Fn: 180
+
+## 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: 5e-06
+- 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: 137
+- num_epochs: 5
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Accuracy | Precision | Recall | F1     | Tp   | Tn   | Fp  | Fn  |
+|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:----:|:----:|:---:|:---:|
+| 0.6841        | 0.2432 | 27   | 0.6509          | 0.6088   | 0.5711    | 0.6129 | 0.5913 | 1004 | 1156 | 754 | 634 |
+| 0.6551        | 0.4865 | 54   | 0.6145          | 0.6700   | 0.6292    | 0.6941 | 0.6601 | 1137 | 1240 | 670 | 501 |
+| 0.5709        | 0.7297 | 81   | 0.6052          | 0.6750   | 0.6174    | 0.7784 | 0.6886 | 1275 | 1120 | 790 | 363 |
+| 0.4953        | 0.9730 | 108  | 0.5217          | 0.7709   | 0.6878    | 0.9225 | 0.7880 | 1511 | 1224 | 686 | 127 |
+| 0.4121        | 1.2162 | 135  | 0.4447          | 0.8588   | 0.8118    | 0.9035 | 0.8552 | 1480 | 1567 | 343 | 158 |
+| 0.3688        | 1.4595 | 162  | 0.4108          | 0.8557   | 0.8043    | 0.9084 | 0.8532 | 1488 | 1548 | 362 | 150 |
+| 0.3300        | 1.7027 | 189  | 0.4537          | 0.7889   | 0.7014    | 0.9451 | 0.8052 | 1548 | 1251 | 659 | 90  |
+| 0.3324        | 1.9459 | 216  | 0.3450          | 0.9039   | 0.8947    | 0.8974 | 0.8961 | 1470 | 1737 | 173 | 168 |
+| 0.3033        | 2.1892 | 243  | 0.4286          | 0.8081   | 0.7216    | 0.9512 | 0.8206 | 1558 | 1309 | 601 | 80  |
+| 0.3007        | 2.4324 | 270  | 0.3362          | 0.9056   | 0.9095    | 0.8834 | 0.8963 | 1447 | 1766 | 144 | 191 |
+| 0.2940        | 2.6757 | 297  | 0.3404          | 0.8867   | 0.8388    | 0.9341 | 0.8839 | 1530 | 1616 | 294 | 108 |
+| 0.2891        | 2.9189 | 324  | 0.2897          | 0.9228   | 0.9231    | 0.9084 | 0.9157 | 1488 | 1786 | 124 | 150 |
+| 0.2921        | 3.1622 | 351  | 0.3451          | 0.8881   | 0.9042    | 0.8474 | 0.8749 | 1388 | 1763 | 147 | 250 |
+| 0.2958        | 3.4054 | 378  | 0.3503          | 0.8816   | 0.8604    | 0.8877 | 0.8738 | 1454 | 1674 | 236 | 184 |
+| 0.2673        | 3.6486 | 405  | 0.3124          | 0.9073   | 0.8834    | 0.9206 | 0.9016 | 1508 | 1711 | 199 | 130 |
+| 0.2755        | 3.8919 | 432  | 0.3070          | 0.9104   | 0.9099    | 0.8944 | 0.9021 | 1465 | 1765 | 145 | 173 |
+| 0.2913        | 4.1351 | 459  | 0.3094          | 0.9101   | 0.8914    | 0.9170 | 0.9040 | 1502 | 1727 | 183 | 136 |
+| 0.2720        | 4.3784 | 486  | 0.3083          | 0.8952   | 0.9283    | 0.8376 | 0.8806 | 1372 | 1804 | 106 | 266 |
+| 0.2929        | 4.6216 | 513  | 0.2726          | 0.9225   | 0.9565    | 0.8718 | 0.9122 | 1428 | 1845 | 65  | 210 |
+| 0.2599        | 4.8649 | 540  | 0.3409          | 0.8904   | 0.8746    | 0.8901 | 0.8823 | 1458 | 1701 | 209 | 180 |
+
+
+### Framework versions
+
+- Transformers 5.0.0
+- Pytorch 2.10.0+cu128
+- Datasets 4.0.0
+- Tokenizers 0.22.2

config.json

@@ -0,0 +1,33 @@
+{
+  "architectures": [
+    "MobileNetV2ForImageClassification"
+  ],
+  "classifier_dropout_prob": 0.2,
+  "depth_divisible_by": 8,
+  "depth_multiplier": 1.0,
+  "dtype": "float32",
+  "expand_ratio": 6,
+  "finegrained_output": true,
+  "first_layer_is_expansion": true,
+  "hidden_act": "relu6",
+  "id2label": {
+    "0": "0",
+    "1": "1"
+  },
+  "image_size": 224,
+  "initializer_range": 0.02,
+  "label2id": {
+    "0": 0,
+    "1": 1
+  },
+  "layer_norm_eps": 0.001,
+  "min_depth": 8,
+  "model_type": "mobilenet_v2",
+  "num_channels": 3,
+  "output_stride": 32,
+  "problem_type": "single_label_classification",
+  "semantic_loss_ignore_index": 255,
+  "tf_padding": true,
+  "transformers_version": "5.0.0",
+  "use_cache": false
+}

model.safetensors

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+version https://git-lfs.github.com/spec/v1
+oid sha256:d6e9644d68cf097846ddac5c08ca36f23f8e7ad9770058bd4d332fc127e8bce2
+size 9080216

preprocessor_config.json

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+{
+  "crop_size": {
+    "height": 224,
+    "width": 224
+  },
+  "data_format": "channels_first",
+  "do_center_crop": true,
+  "do_normalize": true,
+  "do_reduce_labels": false,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.5,
+    0.5,
+    0.5
+  ],
+  "image_processor_type": "MobileNetV2ImageProcessorFast",
+  "image_std": [
+    0.5,
+    0.5,
+    0.5
+  ],
+  "resample": 2,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 256
+  }
+}

training_args.bin

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+version https://git-lfs.github.com/spec/v1
+oid sha256:9718d31a58ba43fb20b11cd760cd66a129ccd3519ce7e56f71efe4a0dad8c9a2
+size 5137