End of training

README.md

@@ -1,27 +1,119 @@
 ---
-license: mit
+library_name: transformers
+license: apache-2.0
+base_model: microsoft/swinv2-base-patch4-window8-256
 tags:
-- ml-intern
+- generated_from_trainer
+datasets:
+- generator
+metrics:
+- accuracy
+- f1
+model-index:
+- name: TN5000_model
+  results:
+  - task:
+      name: Image Classification
+      type: image-classification
+    dataset:
+      name: generator
+      type: generator
+      config: default
+      split: train
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.872
+    - name: F1
+      type: f1
+      value: 0.9080459770114943
 ---
 
-# Johnyquest7/TN5000_model
+<!-- 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. -->
 
-<!-- ml-intern-provenance -->
-## Generated by ML Intern
+# TN5000_model
 
-This model repository was generated by [ML Intern](https://github.com/huggingface/ml-intern), an agent for machine learning research and development on the Hugging Face Hub.
+This model is a fine-tuned version of [microsoft/swinv2-base-patch4-window8-256](https://huggingface.co/microsoft/swinv2-base-patch4-window8-256) on the generator dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1293
+- Accuracy: 0.872
+- F1: 0.9080
+- Sensitivity: 0.8745
+- Specificity: 0.8654
+- Ppv: 0.9442
+- Npv: 0.7258
+- Auc Roc: 0.9367
+- Tp: 474
+- Tn: 180
+- Fp: 28
+- Fn: 68
 
-- Try ML Intern: https://smolagents-ml-intern.hf.space
-- Source code: https://github.com/huggingface/ml-intern
+## Model description
 
-## Usage
+More information needed
 
-```python
-from transformers import AutoModelForCausalLM, AutoTokenizer
+## Intended uses & limitations
 
-model_id = 'Johnyquest7/TN5000_model'
-tokenizer = AutoTokenizer.from_pretrained(model_id)
-model = AutoModelForCausalLM.from_pretrained(model_id)
-```
+More information needed
 
-For non-causal architectures, replace `AutoModelForCausalLM` with the appropriate `AutoModel` class.
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 2e-05
+- train_batch_size: 16
+- eval_batch_size: 16
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 32
+- 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: 0.1
+- num_epochs: 30
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Sensitivity | Specificity | Ppv    | Npv    | Auc Roc | Tp  | Tn  | Fp | Fn  |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:-----------:|:-----------:|:------:|:------:|:-------:|:---:|:---:|:--:|:---:|
+| 0.3555        | 1.0   | 88   | 0.2034          | 0.6786   | 0.7604 | 0.714       | 0.59        | 0.8132 | 0.4521 | 0.7130  | 357 | 118 | 82 | 143 |
+| 0.2755        | 2.0   | 176  | 0.1604          | 0.7314   | 0.7920 | 0.716       | 0.77        | 0.8861 | 0.5203 | 0.8209  | 358 | 154 | 46 | 142 |
+| 0.2580        | 3.0   | 264  | 0.1648          | 0.8143   | 0.8684 | 0.858       | 0.705       | 0.8791 | 0.6651 | 0.8609  | 429 | 141 | 59 | 71  |
+| 0.2399        | 4.0   | 352  | 0.1343          | 0.7686   | 0.8208 | 0.742       | 0.835       | 0.9183 | 0.5642 | 0.8774  | 371 | 167 | 33 | 129 |
+| 0.2292        | 5.0   | 440  | 0.1547          | 0.8757   | 0.9153 | 0.94        | 0.715       | 0.8918 | 0.8266 | 0.9116  | 470 | 143 | 57 | 30  |
+| 0.2285        | 6.0   | 528  | 0.1153          | 0.8186   | 0.8656 | 0.818       | 0.82        | 0.9191 | 0.6431 | 0.9161  | 409 | 164 | 36 | 91  |
+| 0.2417        | 7.0   | 616  | 0.1111          | 0.8171   | 0.8621 | 0.8         | 0.86        | 0.9346 | 0.6324 | 0.9171  | 400 | 172 | 28 | 100 |
+| 0.1748        | 8.0   | 704  | 0.1145          | 0.8514   | 0.8919 | 0.858       | 0.835       | 0.9286 | 0.7017 | 0.9271  | 429 | 167 | 33 | 71  |
+| 0.1901        | 9.0   | 792  | 0.1489          | 0.8857   | 0.9206 | 0.928       | 0.78        | 0.9134 | 0.8125 | 0.9208  | 464 | 156 | 44 | 36  |
+| 0.1872        | 10.0  | 880  | 0.1162          | 0.8514   | 0.8919 | 0.858       | 0.835       | 0.9286 | 0.7017 | 0.9218  | 429 | 167 | 33 | 71  |
+| 0.1439        | 11.0  | 968  | 0.1108          | 0.8014   | 0.8478 | 0.774       | 0.87        | 0.9370 | 0.6063 | 0.9259  | 387 | 174 | 26 | 113 |
+| 0.1868        | 12.0  | 1056 | 0.1185          | 0.8714   | 0.9076 | 0.884       | 0.84        | 0.9325 | 0.7434 | 0.9320  | 442 | 168 | 32 | 58  |
+| 0.2002        | 13.0  | 1144 | 0.1376          | 0.8857   | 0.9205 | 0.926       | 0.785       | 0.9150 | 0.8093 | 0.9317  | 463 | 157 | 43 | 37  |
+| 0.2023        | 14.0  | 1232 | 0.1339          | 0.8857   | 0.9195 | 0.914       | 0.815       | 0.9251 | 0.7913 | 0.9350  | 457 | 163 | 37 | 43  |
+| 0.1582        | 15.0  | 1320 | 0.1346          | 0.8929   | 0.9252 | 0.928       | 0.805       | 0.9225 | 0.8173 | 0.9338  | 464 | 161 | 39 | 36  |
+| 0.1488        | 16.0  | 1408 | 0.1319          | 0.8957   | 0.9266 | 0.922       | 0.83        | 0.9313 | 0.8098 | 0.9366  | 461 | 166 | 34 | 39  |
+| 0.1249        | 17.0  | 1496 | 0.1280          | 0.87     | 0.9061 | 0.878       | 0.85        | 0.9360 | 0.7359 | 0.9370  | 439 | 170 | 30 | 61  |
+| 0.1553        | 18.0  | 1584 | 0.1121          | 0.8571   | 0.8943 | 0.846       | 0.885       | 0.9484 | 0.6969 | 0.9390  | 423 | 177 | 23 | 77  |
+| 0.1083        | 19.0  | 1672 | 0.1675          | 0.9029   | 0.9331 | 0.948       | 0.79        | 0.9186 | 0.8587 | 0.9381  | 474 | 158 | 42 | 26  |
+| 0.1379        | 20.0  | 1760 | 0.1535          | 0.9      | 0.9308 | 0.942       | 0.795       | 0.9199 | 0.8457 | 0.9340  | 471 | 159 | 41 | 29  |
+| 0.1458        | 21.0  | 1848 | 0.1915          | 0.9043   | 0.9344 | 0.954       | 0.78        | 0.9155 | 0.8715 | 0.9345  | 477 | 156 | 44 | 23  |
+| 0.1322        | 22.0  | 1936 | 0.1244          | 0.8786   | 0.9126 | 0.888       | 0.855       | 0.9387 | 0.7533 | 0.9399  | 444 | 171 | 29 | 56  |
+| 0.1438        | 23.0  | 2024 | 0.1519          | 0.8757   | 0.9122 | 0.904       | 0.805       | 0.9206 | 0.7703 | 0.9356  | 452 | 161 | 39 | 48  |
+| 0.1265        | 24.0  | 2112 | 0.1421          | 0.8871   | 0.9204 | 0.914       | 0.82        | 0.9270 | 0.7923 | 0.9378  | 457 | 164 | 36 | 43  |
+| 0.1118        | 25.0  | 2200 | 0.2165          | 0.9057   | 0.9358 | 0.962       | 0.765       | 0.9110 | 0.8895 | 0.9380  | 481 | 153 | 47 | 19  |
+| 0.0971        | 26.0  | 2288 | 0.1557          | 0.8857   | 0.9194 | 0.912       | 0.82        | 0.9268 | 0.7885 | 0.9342  | 456 | 164 | 36 | 44  |
+| 0.1235        | 27.0  | 2376 | 0.1394          | 0.88     | 0.9143 | 0.896       | 0.84        | 0.9333 | 0.7636 | 0.9376  | 448 | 168 | 32 | 52  |
+
+
+### Framework versions
+
+- Transformers 5.8.0
+- Pytorch 2.11.0+cu130
+- Datasets 4.8.5
+- Tokenizers 0.22.2

config.json

@@ -0,0 +1,67 @@
+{
+  "architectures": [
+    "Swinv2ForImageClassification"
+  ],
+  "attention_probs_dropout_prob": 0.0,
+  "depths": [
+    2,
+    2,
+    18,
+    2
+  ],
+  "drop_path_rate": 0.1,
+  "dtype": "float32",
+  "embed_dim": 128,
+  "encoder_stride": 32,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.0,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "benign",
+    "1": "malignant"
+  },
+  "image_size": 256,
+  "initializer_range": 0.02,
+  "label2id": {
+    "benign": "0",
+    "malignant": "1"
+  },
+  "layer_norm_eps": 1e-05,
+  "mlp_ratio": 4.0,
+  "model_type": "swinv2",
+  "num_channels": 3,
+  "num_heads": [
+    4,
+    8,
+    16,
+    32
+  ],
+  "num_layers": 4,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "patch_size": 4,
+  "path_norm": true,
+  "pretrained_window_sizes": [
+    0,
+    0,
+    0,
+    0
+  ],
+  "problem_type": "single_label_classification",
+  "qkv_bias": true,
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "transformers_version": "5.8.0",
+  "use_absolute_embeddings": false,
+  "use_cache": false,
+  "window_size": 8
+}

metrics_summary.json

@@ -0,0 +1,58 @@
+{
+  "model": "microsoft/swinv2-base-patch4-window8-256",
+  "dataset": "TN5000",
+  "validation": {
+    "loss": 0.12442023307085037,
+    "accuracy": 0.8785714285714286,
+    "f1": 0.9126413155190134,
+    "sensitivity": 0.888,
+    "specificity": 0.855,
+    "ppv": 0.9386892177589852,
+    "npv": 0.7533039647577092,
+    "auc_roc": 0.93988,
+    "tp": 444,
+    "tn": 171,
+    "fp": 29,
+    "fn": 56,
+    "runtime": 4.4047,
+    "samples_per_second": 158.921,
+    "steps_per_second": 9.989
+  },
+  "test": {
+    "loss": 0.12932181358337402,
+    "accuracy": 0.872,
+    "f1": 0.9080459770114943,
+    "sensitivity": 0.8745387453874539,
+    "specificity": 0.8653846153846154,
+    "ppv": 0.9442231075697212,
+    "npv": 0.7258064516129032,
+    "auc_roc": 0.9366839341470338,
+    "tp": 474,
+    "tn": 180,
+    "fp": 28,
+    "fn": 68,
+    "runtime": 4.6692,
+    "samples_per_second": 160.627,
+    "steps_per_second": 10.066
+  },
+  "confusion_matrix_validation": {
+    "tp": 444,
+    "tn": 171,
+    "fp": 29,
+    "fn": 56
+  },
+  "confusion_matrix_test": {
+    "tp": 474,
+    "tn": 180,
+    "fp": 28,
+    "fn": 68
+  },
+  "class_weights": [
+    1.7543859649122806,
+    0.6993006993006993
+  ],
+  "label_names": [
+    "benign",
+    "malignant"
+  ]
+}

model.safetensors

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+version https://git-lfs.github.com/spec/v1
+oid sha256:848fd08c904c3ffdde5f8916e673d8fd20494447fd62252f701688f5e676a959
+size 347645480

preprocessor_config.json

@@ -0,0 +1,22 @@
+{
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ViTImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "height": 256,
+    "width": 256
+  }
+}

training_args.bin

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+size 5329