Model save

README.md

@@ -3,11 +3,26 @@ license: apache-2.0
 base_model: google/vit-base-patch16-224-in21k
 tags:
 - generated_from_trainer
+datasets:
+- chestxrayclassification
 metrics:
 - accuracy
 model-index:
 - name: pneumonia-classification-model
-  results: []
+  results:
+  - task:
+      name: Image Classification
+      type: image-classification
+    dataset:
+      name: chestxrayclassification
+      type: chestxrayclassification
+      config: full
+      split: train
+      args: full
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.9632352941176471
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -15,10 +30,10 @@ should probably proofread and complete it, then remove this comment. -->
 
 # pneumonia-classification-model
 
-This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on an unknown dataset.
+This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the chestxrayclassification dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.2141
-- Accuracy: 0.9338
+- Loss: 0.1081
+- Accuracy: 0.9632
 
 ## Model description
 
@@ -38,26 +53,41 @@ More information needed
 
 The following hyperparameters were used during training:
 - learning_rate: 5e-05
-- train_batch_size: 16
-- eval_batch_size: 16
+- train_batch_size: 32
+- eval_batch_size: 32
 - seed: 42
 - gradient_accumulation_steps: 4
-- total_train_batch_size: 64
+- total_train_batch_size: 128
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
 - lr_scheduler_warmup_ratio: 0.1
-- num_epochs: 1
+- num_epochs: 16
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 0.3717        | 1.0   | 51   | 0.2141          | 0.9338   |
+| 0.5968        | 0.98  | 25   | 0.4404          | 0.7230   |
+| 0.3253        | 2.0   | 51   | 0.2667          | 0.9130   |
+| 0.2096        | 2.98  | 76   | 0.2183          | 0.9093   |
+| 0.1623        | 4.0   | 102  | 0.1786          | 0.9387   |
+| 0.1697        | 4.98  | 127  | 0.1354          | 0.9522   |
+| 0.1405        | 6.0   | 153  | 0.1424          | 0.9510   |
+| 0.1306        | 6.98  | 178  | 0.1299          | 0.9534   |
+| 0.1093        | 8.0   | 204  | 0.1316          | 0.9510   |
+| 0.1151        | 8.98  | 229  | 0.1179          | 0.9583   |
+| 0.0976        | 10.0  | 255  | 0.1204          | 0.9583   |
+| 0.0932        | 10.98 | 280  | 0.1393          | 0.9485   |
+| 0.1039        | 12.0  | 306  | 0.1239          | 0.9571   |
+| 0.0907        | 12.98 | 331  | 0.1029          | 0.9583   |
+| 0.0917        | 14.0  | 357  | 0.1275          | 0.9583   |
+| 0.0754        | 14.98 | 382  | 0.1034          | 0.9669   |
+| 0.0662        | 15.69 | 400  | 0.1081          | 0.9632   |
 
 
 ### Framework versions
 
-- Transformers 4.38.2
-- Pytorch 2.1.0+cu121
-- Datasets 2.18.0
+- Transformers 4.38.1
+- Pytorch 2.1.2
+- Datasets 2.1.0
 - Tokenizers 0.15.2

model.safetensors

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