End of training

README.md

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+---
+base_model: juliensimon/autotrain-chest-xray-demo-1677859324
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+- precision
+- recall
+model-index:
+- name: Text2Image_PyData_23
+  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. -->
+
+# Text2Image_PyData_23
+
+This model is a fine-tuned version of [juliensimon/autotrain-chest-xray-demo-1677859324](https://huggingface.co/juliensimon/autotrain-chest-xray-demo-1677859324) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.3421
+- Accuracy: 0.8333
+- F1: [0.71584699 0.88208617]
+- Precision: [0.99242424 0.79065041]
+- Recall: [0.55982906 0.9974359 ]
+
+## 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: 1e-05
+- train_batch_size: 16
+- eval_batch_size: 64
+- seed: 42
+- gradient_accumulation_steps: 8
+- total_train_batch_size: 128
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 15
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1                      | Precision               | Recall                  |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------------------:|:-----------------------:|:-----------------------:|
+| 0.0451        | 0.98  | 40   | 0.6974          | 0.7933   | [0.62170088 0.85777288] | [0.99065421 0.75241779] | [0.45299145 0.9974359 ] |
+| 0.036         | 1.99  | 81   | 0.3557          | 0.8958   | [0.84107579 0.92252682] | [0.98285714 0.86191537] | [0.73504274 0.99230769] |
+| 0.043         | 2.99  | 122  | 0.4253          | 0.9006   | [0.84803922 0.92619048] | [0.99425287 0.86444444] | [0.73931624 0.9974359 ] |
+| 0.0225        | 4.0   | 163  | 0.8776          | 0.8349   | [0.71934605 0.8830874 ] | [0.9924812  0.79226069] | [0.56410256 0.9974359 ] |
+| 0.0153        | 4.98  | 203  | 0.7095          | 0.8670   | [0.78552972 0.90360046] | [0.99346405 0.82590234] | [0.64957265 0.9974359 ] |
+| 0.0107        | 5.99  | 244  | 0.8537          | 0.8446   | [0.73994638 0.88914286] | [0.99280576 0.80206186] | [0.58974359 0.9974359 ] |
+| 0.0052        | 6.99  | 285  | 1.0167          | 0.8462   | [0.74331551 0.89016018] | [0.99285714 0.80371901] | [0.59401709 0.9974359 ] |
+| 0.0049        | 8.0   | 326  | 1.3230          | 0.8045   | [0.64942529 0.86444444] | [0.99122807 0.7627451 ] | [0.48290598 0.9974359 ] |
+| 0.0061        | 8.98  | 366  | 1.2652          | 0.8269   | [0.70165746 0.87810384] | [0.9921875  0.78427419] | [0.54273504 0.9974359 ] |
+| 0.004         | 9.99  | 407  | 1.4846          | 0.8157   | [0.67605634 0.8712206 ] | [0.99173554 0.77335984] | [0.51282051 0.9974359 ] |
+| 0.0005        | 10.99 | 448  | 1.5685          | 0.8109   | [0.66477273 0.86830357] | [0.99152542 0.7687747 ] | [0.5       0.9974359]   |
+| 0.0029        | 12.0  | 489  | 1.2547          | 0.8397   | [0.72972973 0.88610478] | [0.99264706 0.79713115] | [0.57692308 0.9974359 ] |
+| 0.0015        | 12.98 | 529  | 1.4026          | 0.8285   | [0.70523416 0.87909605] | [0.99224806 0.78585859] | [0.54700855 0.9974359 ] |
+| 0.0012        | 13.99 | 570  | 1.4444          | 0.8237   | [0.69444444 0.87612613] | [0.99206349 0.7811245 ] | [0.53418803 0.9974359 ] |
+| 0.0039        | 14.72 | 600  | 1.3421          | 0.8333   | [0.71584699 0.88208617] | [0.99242424 0.79065041] | [0.55982906 0.9974359 ] |
+
+
+### Framework versions
+
+- Transformers 4.34.1
+- Pytorch 2.1.0+cu118
+- Datasets 2.14.6
+- Tokenizers 0.14.1

config.json

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+{
+  "_name_or_path": "juliensimon/autotrain-chest-xray-demo-1677859324",
+  "architectures": [
+    "SwinForImageClassification"
+  ],
+  "attention_probs_dropout_prob": 0.0,
+  "depths": [
+    2,
+    2,
+    18,
+    2
+  ],
+  "drop_path_rate": 0.1,
+  "embed_dim": 128,
+  "encoder_stride": 32,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.0,
+  "hidden_size": 1024,
+  "id2label": {
+    "0": "NORMAL",
+    "1": "PNEUMONIA"
+  },
+  "image_size": 224,
+  "initializer_range": 0.02,
+  "label2id": {
+    "NORMAL": "0",
+    "PNEUMONIA": "1"
+  },
+  "layer_norm_eps": 1e-05,
+  "max_length": 128,
+  "mlp_ratio": 4.0,
+  "model_type": "swin",
+  "num_channels": 3,
+  "num_heads": [
+    4,
+    8,
+    16,
+    32
+  ],
+  "num_layers": 4,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "padding": "max_length",
+  "patch_size": 4,
+  "path_norm": true,
+  "problem_type": "single_label_classification",
+  "qkv_bias": true,
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "torch_dtype": "float32",
+  "transformers_version": "4.34.1",
+  "use_absolute_embeddings": false,
+  "window_size": 7
+}

preprocessor_config.json

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+{
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "feature_extractor_type": "ViTFeatureExtractor",
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ViTFeatureExtractor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "height": 224,
+    "width": 224
+  }
+}

pytorch_model.bin

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+oid sha256:c9ade60aa9e2d4a51f5b214cb1f7ddf6cfcbed58a8e1615520f77ff7a2212b6f
+size 347600206

training_args.bin

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+size 4536