Model save

README.md

@@ -5,9 +5,36 @@ tags:
 - generated_from_trainer
 datasets:
 - imagefolder
+metrics:
+- accuracy
+- f1
+- recall
+- precision
 model-index:
 - name: vit-base-patch16-224-in21k_covid_19_ct_scans
-  results: []
+  results:
+  - task:
+      name: Image Classification
+      type: image-classification
+    dataset:
+      name: imagefolder
+      type: imagefolder
+      config: default
+      split: train
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.9765258215962441
+    - name: F1
+      type: f1
+      value: 0.9294374875770225
+    - name: Recall
+      type: recall
+      value: 1.0
+    - name: Precision
+      type: precision
+      value: 0.9744897959183674
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -17,17 +44,12 @@ should probably proofread and complete it, then remove this comment. -->
 
 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 imagefolder dataset.
 It achieves the following results on the evaluation set:
-- eval_loss: 0.2255
-- eval_accuracy: 0.9671
-- eval_F1: 0.9163
-- eval_AUC: 0.8704
-- eval_Recall: 1.0
-- eval_Precision: 0.9637
-- eval_runtime: 4.1611
-- eval_samples_per_second: 51.189
-- eval_steps_per_second: 3.365
-- epoch: 20.0
-- step: 1080
+- Loss: 0.1064
+- Accuracy: 0.9765
+- F1: 0.9294
+- Auc: 0.8864
+- Recall: 1.0
+- Precision: 0.9745
 
 ## Model description
 
@@ -52,7 +74,25 @@ The following hyperparameters were used during training:
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- num_epochs: 100
+- num_epochs: 12
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Auc    | Recall | Precision |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:------:|:---------:|
+| 0.6804        | 1.0   | 54   | 0.3821          | 0.8967   | 0.4728 | 0.5    | 1.0    | 0.8967    |
+| 0.6804        | 2.0   | 108  | 0.4134          | 0.8967   | 0.4728 | 0.5    | 1.0    | 0.8967    |
+| 0.6804        | 3.0   | 162  | 0.2708          | 0.9061   | 0.5585 | 0.5455 | 1.0    | 0.9052    |
+| 0.6804        | 4.0   | 216  | 0.2405          | 0.9437   | 0.7973 | 0.7273 | 1.0    | 0.9409    |
+| 0.6804        | 5.0   | 270  | 0.2193          | 0.9437   | 0.7973 | 0.7273 | 1.0    | 0.9409    |
+| 0.6804        | 6.0   | 324  | 0.1719          | 0.9484   | 0.8775 | 0.9310 | 0.9529 | 0.9891    |
+| 0.6804        | 7.0   | 378  | 0.0525          | 0.9859   | 0.9612 | 0.9519 | 0.9948 | 0.9896    |
+| 0.6804        | 8.0   | 432  | 0.0482          | 0.9906   | 0.9736 | 0.9545 | 1.0    | 0.9896    |
+| 0.6804        | 9.0   | 486  | 0.0907          | 0.9765   | 0.9294 | 0.8864 | 1.0    | 0.9745    |
+| 0.1258        | 10.0  | 540  | 0.1009          | 0.9765   | 0.9294 | 0.8864 | 1.0    | 0.9745    |
+| 0.1258        | 11.0  | 594  | 0.1051          | 0.9765   | 0.9294 | 0.8864 | 1.0    | 0.9745    |
+| 0.1258        | 12.0  | 648  | 0.1064          | 0.9765   | 0.9294 | 0.8864 | 1.0    | 0.9745    |
+
 
 ### Framework versions
 

model.safetensors

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 size 343223968

runs/May28_13-21-32_RTX3090/events.out.tfevents.1716870093.RTX3090.312878.0

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