End of training

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: facebook/deit-small-patch16-224
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- precision
+- recall
+- f1
+model-index:
+- name: DeiT_S16_RF_Spectrogram
+  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. -->
+
+# DeiT_S16_RF_Spectrogram
+
+This model is a fine-tuned version of [facebook/deit-small-patch16-224](https://huggingface.co/facebook/deit-small-patch16-224) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0669
+- Accuracy: 0.9882
+- Precision: 0.9926
+- Recall: 0.9817
+- F1: 0.9871
+- Tp: 1608
+- Tn: 1898
+- Fp: 12
+- Fn: 30
+
+## 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-05
+- train_batch_size: 32
+- eval_batch_size: 32
+- 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: 1107
+- num_epochs: 10
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Accuracy | Precision | Recall | F1     | Tp   | Tn   | Fp | Fn  |
+|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:----:|:----:|:--:|:---:|
+| 0.4745        | 0.2477 | 110  | 0.1945          | 0.9340   | 0.9875    | 0.8681 | 0.9240 | 1422 | 1892 | 18 | 216 |
+| 0.1543        | 0.4955 | 220  | 0.1073          | 0.9684   | 1.0       | 0.9316 | 0.9646 | 1526 | 1910 | 0  | 112 |
+| 0.0972        | 0.7432 | 330  | 0.0959          | 0.9791   | 0.9943    | 0.9603 | 0.9770 | 1573 | 1901 | 9  | 65  |
+| 0.0967        | 0.9910 | 440  | 0.0601          | 0.9859   | 0.9969    | 0.9725 | 0.9845 | 1593 | 1905 | 5  | 45  |
+| 0.0763        | 1.2387 | 550  | 0.0586          | 0.9856   | 0.9969    | 0.9719 | 0.9842 | 1592 | 1905 | 5  | 46  |
+| 0.0634        | 1.4865 | 660  | 0.0935          | 0.9755   | 0.9630    | 0.9847 | 0.9737 | 1613 | 1848 | 62 | 25  |
+| 0.0854        | 1.7342 | 770  | 0.0607          | 0.9848   | 0.9919    | 0.9750 | 0.9834 | 1597 | 1897 | 13 | 41  |
+| 0.0834        | 1.9820 | 880  | 0.0684          | 0.9828   | 0.9852    | 0.9774 | 0.9813 | 1601 | 1886 | 24 | 37  |
+| 0.0545        | 2.2297 | 990  | 0.0705          | 0.9831   | 0.9981    | 0.9652 | 0.9814 | 1581 | 1907 | 3  | 57  |
+| 0.0728        | 2.4775 | 1100 | 0.0594          | 0.9845   | 0.9962    | 0.9701 | 0.9830 | 1589 | 1904 | 6  | 49  |
+| 0.0781        | 2.7252 | 1210 | 0.0571          | 0.9868   | 0.9994    | 0.9719 | 0.9855 | 1592 | 1909 | 1  | 46  |
+| 0.0686        | 2.9730 | 1320 | 0.0583          | 0.9868   | 0.9901    | 0.9811 | 0.9856 | 1607 | 1894 | 16 | 31  |
+| 0.0683        | 3.2207 | 1430 | 0.0486          | 0.9890   | 0.9994    | 0.9768 | 0.9880 | 1600 | 1909 | 1  | 38  |
+| 0.0505        | 3.4685 | 1540 | 0.0539          | 0.9865   | 0.9932    | 0.9774 | 0.9852 | 1601 | 1899 | 11 | 37  |
+| 0.0610        | 3.7162 | 1650 | 0.0559          | 0.9882   | 0.9981    | 0.9762 | 0.9870 | 1599 | 1907 | 3  | 39  |
+| 0.0629        | 3.9640 | 1760 | 0.0432          | 0.9901   | 0.9975    | 0.9811 | 0.9892 | 1607 | 1906 | 4  | 31  |
+| 0.0525        | 4.2117 | 1870 | 0.0465          | 0.9896   | 0.9994    | 0.9780 | 0.9886 | 1602 | 1909 | 1  | 36  |
+| 0.0464        | 4.4595 | 1980 | 0.0502          | 0.9887   | 0.9950    | 0.9805 | 0.9877 | 1606 | 1902 | 8  | 32  |
+| 0.0543        | 4.7072 | 2090 | 0.0454          | 0.9896   | 0.9969    | 0.9805 | 0.9886 | 1606 | 1905 | 5  | 32  |
+| 0.0495        | 4.9550 | 2200 | 0.0453          | 0.9904   | 0.9969    | 0.9823 | 0.9895 | 1609 | 1905 | 5  | 29  |
+| 0.0400        | 5.2027 | 2310 | 0.0512          | 0.9890   | 0.9957    | 0.9805 | 0.9880 | 1606 | 1903 | 7  | 32  |
+| 0.0339        | 5.4505 | 2420 | 0.0514          | 0.9893   | 0.9963    | 0.9805 | 0.9883 | 1606 | 1904 | 6  | 32  |
+| 0.0356        | 5.6982 | 2530 | 0.0449          | 0.9899   | 0.9963    | 0.9817 | 0.9889 | 1608 | 1904 | 6  | 30  |
+| 0.0363        | 5.9459 | 2640 | 0.0521          | 0.9859   | 0.9824    | 0.9872 | 0.9848 | 1617 | 1881 | 29 | 21  |
+| 0.0273        | 6.1937 | 2750 | 0.0499          | 0.9893   | 0.9914    | 0.9853 | 0.9884 | 1614 | 1896 | 14 | 24  |
+| 0.0236        | 6.4414 | 2860 | 0.0542          | 0.9884   | 0.9920    | 0.9829 | 0.9874 | 1610 | 1897 | 13 | 28  |
+| 0.0313        | 6.6892 | 2970 | 0.0440          | 0.9910   | 0.9981    | 0.9823 | 0.9902 | 1609 | 1907 | 3  | 29  |
+| 0.0298        | 6.9369 | 3080 | 0.0511          | 0.9913   | 0.9981    | 0.9829 | 0.9905 | 1610 | 1907 | 3  | 28  |
+| 0.0193        | 7.1847 | 3190 | 0.0531          | 0.9887   | 0.9920    | 0.9835 | 0.9877 | 1611 | 1897 | 13 | 27  |
+| 0.0245        | 7.4324 | 3300 | 0.0529          | 0.9893   | 0.9938    | 0.9829 | 0.9883 | 1610 | 1900 | 10 | 28  |
+| 0.0234        | 7.6802 | 3410 | 0.0640          | 0.9882   | 0.9920    | 0.9823 | 0.9871 | 1609 | 1897 | 13 | 29  |
+| 0.0172        | 7.9279 | 3520 | 0.0636          | 0.9896   | 0.9963    | 0.9811 | 0.9886 | 1607 | 1904 | 6  | 31  |
+| 0.0231        | 8.1757 | 3630 | 0.0559          | 0.9890   | 0.9932    | 0.9829 | 0.9880 | 1610 | 1899 | 11 | 28  |
+| 0.0148        | 8.4234 | 3740 | 0.0566          | 0.9893   | 0.9932    | 0.9835 | 0.9883 | 1611 | 1899 | 11 | 27  |
+| 0.0145        | 8.6712 | 3850 | 0.0601          | 0.9890   | 0.9914    | 0.9847 | 0.9881 | 1613 | 1896 | 14 | 25  |
+| 0.0193        | 8.9189 | 3960 | 0.0634          | 0.9899   | 0.9951    | 0.9829 | 0.9889 | 1610 | 1902 | 8  | 28  |
+| 0.0139        | 9.1667 | 4070 | 0.0647          | 0.9896   | 0.9957    | 0.9817 | 0.9886 | 1608 | 1903 | 7  | 30  |
+| 0.0089        | 9.4144 | 4180 | 0.0678          | 0.9893   | 0.9950    | 0.9817 | 0.9883 | 1608 | 1902 | 8  | 30  |
+| 0.0087        | 9.6622 | 4290 | 0.0664          | 0.9893   | 0.9950    | 0.9817 | 0.9883 | 1608 | 1902 | 8  | 30  |
+| 0.0104        | 9.9099 | 4400 | 0.0669          | 0.9882   | 0.9926    | 0.9817 | 0.9871 | 1608 | 1898 | 12 | 30  |
+
+
+### Framework versions
+
+- Transformers 5.0.0
+- Pytorch 2.10.0+cu128
+- Datasets 4.0.0
+- Tokenizers 0.22.2

config.json

@@ -0,0 +1,34 @@
+{
+  "architectures": [
+    "ViTForImageClassification"
+  ],
+  "attention_probs_dropout_prob": 0.0,
+  "dtype": "float32",
+  "encoder_stride": 16,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.0,
+  "hidden_size": 384,
+  "id2label": {
+    "0": "0",
+    "1": "1"
+  },
+  "image_size": 224,
+  "initializer_range": 0.02,
+  "intermediate_size": 1536,
+  "label2id": {
+    "0": 0,
+    "1": 1
+  },
+  "layer_norm_eps": 1e-12,
+  "model_type": "vit",
+  "num_attention_heads": 6,
+  "num_channels": 3,
+  "num_hidden_layers": 12,
+  "patch_size": 16,
+  "pooler_act": "tanh",
+  "pooler_output_size": 384,
+  "problem_type": "single_label_classification",
+  "qkv_bias": true,
+  "transformers_version": "5.0.0",
+  "use_cache": false
+}

model.safetensors

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+version https://git-lfs.github.com/spec/v1
+oid sha256:716896587ca8c7c8295de39adaa2b2fe9a1a96888c8f200e59825fbd6866eff2
+size 86688624

preprocessor_config.json

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+{
+  "do_convert_rgb": null,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.5,
+    0.5,
+    0.5
+  ],
+  "image_processor_type": "ViTImageProcessor",
+  "image_std": [
+    0.5,
+    0.5,
+    0.5
+  ],
+  "resample": 2,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "height": 224,
+    "width": 224
+  }
+}

training_args.bin

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+size 5137