Clasificador de imagenes para saber que grado de demencia existe en la persona

README.md

@@ -2,12 +2,28 @@
 license: apache-2.0
 base_model: microsoft/resnet-50
 tags:
+- image-classification
 - generated_from_trainer
 datasets:
 - imagefolder
+metrics:
+- accuracy
 model-index:
 - name: model-Dementia-classification-Alejandro-Arroyo
-  results: []
+  results:
+  - task:
+      name: Image Classification
+      type: image-classification
+    dataset:
+      name: RiniPL/Dementia_Dataset
+      type: imagefolder
+      config: default
+      split: validation
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.9230769230769231
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -15,7 +31,10 @@ should probably proofread and complete it, then remove this comment. -->
 
 # model-Dementia-classification-Alejandro-Arroyo
 
-This model is a fine-tuned version of [microsoft/resnet-50](https://huggingface.co/microsoft/resnet-50) on the imagefolder dataset.
+This model is a fine-tuned version of [microsoft/resnet-50](https://huggingface.co/microsoft/resnet-50) on the RiniPL/Dementia_Dataset dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1858
+- Accuracy: 0.9231
 
 ## Model description
 

all_results.json

@@ -1,13 +1,13 @@
 {
     "epoch": 20.0,
-    "eval_accuracy": 0.8461538461538461,
-    "eval_loss": 0.40449273586273193,
-    "eval_runtime": 1.2182,
-    "eval_samples_per_second": 53.358,
-    "eval_steps_per_second": 7.388,
+    "eval_accuracy": 0.9230769230769231,
+    "eval_loss": 0.18579737842082977,
+    "eval_runtime": 1.1471,
+    "eval_samples_per_second": 56.665,
+    "eval_steps_per_second": 7.846,
     "total_flos": 1.007413922930688e+17,
-    "train_loss": 0.8283113267686631,
-    "train_runtime": 54.0676,
-    "train_samples_per_second": 24.044,
-    "train_steps_per_second": 3.329
+    "train_loss": 0.5491177876790364,
+    "train_runtime": 52.8429,
+    "train_samples_per_second": 24.601,
+    "train_steps_per_second": 3.406
 }

eval_results.json

@@ -1,8 +1,8 @@
 {
     "epoch": 20.0,
-    "eval_accuracy": 0.8461538461538461,
-    "eval_loss": 0.40449273586273193,
-    "eval_runtime": 1.2182,
-    "eval_samples_per_second": 53.358,
-    "eval_steps_per_second": 7.388
+    "eval_accuracy": 0.9230769230769231,
+    "eval_loss": 0.18579737842082977,
+    "eval_runtime": 1.1471,
+    "eval_samples_per_second": 56.665,
+    "eval_steps_per_second": 7.846
 }

train_results.json

@@ -1,8 +1,8 @@
 {
     "epoch": 20.0,
     "total_flos": 1.007413922930688e+17,
-    "train_loss": 0.8283113267686631,
-    "train_runtime": 54.0676,
-    "train_samples_per_second": 24.044,
-    "train_steps_per_second": 3.329
+    "train_loss": 0.5491177876790364,
+    "train_runtime": 52.8429,
+    "train_samples_per_second": 24.601,
+    "train_steps_per_second": 3.406
 }