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README.md

@@ -1,19 +1,13 @@
 ---
 license: apache-2.0
 tags:
-- image-classification
 - generated_from_trainer
 datasets:
 - beans
 metrics:
 - accuracy
-widget:
-- src: https://huggingface.co/platzi/platzi-vit-model-andres-galvis/blob/main/healthy.jpeg
-  example_title: Healthy
-- src: https://huggingface.co/platzi/platzi-vit-model-andres-galvis/blob/main/bean_rust.jpeg
-  example_title: Bean Rust
 model-index:
-- name: platzi-vit-base-beans
+- name: platzi-vit-model-andres-galvis
   results:
   - task:
       name: Image Classification
@@ -22,12 +16,12 @@ model-index:
       name: beans
       type: beans
       config: default
-      split: train
+      split: validation
       args: default
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.9924812030075187
+      value: 0.9849624060150376
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -37,13 +31,8 @@ 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 beans dataset.
 It achieves the following results on the evaluation set:
-- eval_loss: 1.0829
-- eval_accuracy: 0.3308
-- eval_runtime: 33.5958
-- eval_samples_per_second: 3.959
-- eval_steps_per_second: 0.506
-- epoch: 0.01
-- step: 1
+- Loss: 0.0227
+- Accuracy: 0.9850
 
 ## Model description
 
@@ -70,6 +59,13 @@ The following hyperparameters were used during training:
 - lr_scheduler_type: linear
 - num_epochs: 4
 
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.1343        | 3.85  | 500  | 0.0227          | 0.9850   |
+
+
 ### Framework versions
 
 - Transformers 4.27.3

all_results.json

@@ -1,12 +1,12 @@
 {
-    "epoch": 0.01,
-    "eval_accuracy": 0.3308270676691729,
-    "eval_loss": 1.0828973054885864,
-    "eval_runtime": 33.5958,
-    "eval_samples_per_second": 3.959,
-    "eval_steps_per_second": 0.506,
-    "train_loss": 0.14375279158926926,
-    "train_runtime": 2884.3099,
-    "train_samples_per_second": 1.434,
-    "train_steps_per_second": 0.18
+    "epoch": 4.0,
+    "eval_accuracy": 0.9849624060150376,
+    "eval_loss": 0.02271120436489582,
+    "eval_runtime": 38.2076,
+    "eval_samples_per_second": 3.481,
+    "eval_steps_per_second": 0.445,
+    "train_loss": 0.12937975365381973,
+    "train_runtime": 3342.3263,
+    "train_samples_per_second": 1.237,
+    "train_steps_per_second": 0.156
 }

eval_results.json

@@ -1,8 +1,8 @@
 {
-    "epoch": 0.01,
-    "eval_accuracy": 0.3308270676691729,
-    "eval_loss": 1.0828973054885864,
-    "eval_runtime": 33.5958,
-    "eval_samples_per_second": 3.959,
-    "eval_steps_per_second": 0.506
+    "epoch": 4.0,
+    "eval_accuracy": 0.9849624060150376,
+    "eval_loss": 0.02271120436489582,
+    "eval_runtime": 38.2076,
+    "eval_samples_per_second": 3.481,
+    "eval_steps_per_second": 0.445
 }

pytorch_model.bin

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runs/Mar27_20-02-23_aleuse/1679965690.8306394/events.out.tfevents.1679965690.aleuse.8064.2

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runs/Mar27_20-02-23_aleuse/events.out.tfevents.1679969426.aleuse.8064.3

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train_results.json

@@ -1,7 +1,7 @@
 {
     "epoch": 4.0,
-    "train_loss": 0.14375279158926926,
-    "train_runtime": 2884.3099,
-    "train_samples_per_second": 1.434,
-    "train_steps_per_second": 0.18
+    "train_loss": 0.12937975365381973,
+    "train_runtime": 3342.3263,
+    "train_samples_per_second": 1.237,
+    "train_steps_per_second": 0.156
 }