tejp/test_train

README.md

@@ -2,12 +2,32 @@
 license: apache-2.0
 base_model: google/vit-base-patch16-224
 tags:
+- image-classification
 - generated_from_trainer
 datasets:
 - imagefolder
+metrics:
+- accuracy
+- f1
 model-index:
 - name: fine-tuned-augmented
-  results: []
+  results:
+  - task:
+      name: Image Classification
+      type: image-classification
+    dataset:
+      name: test_train
+      type: imagefolder
+      config: default
+      split: test
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 1.0
+    - name: F1
+      type: f1
+      value: 1.0
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -15,7 +35,11 @@ should probably proofread and complete it, then remove this comment. -->
 
 # fine-tuned-augmented
 
-This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the imagefolder dataset.
+This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the test_train dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0120
+- Accuracy: 1.0
+- F1: 1.0
 
 ## Model description
 

all_results.json

@@ -1,14 +1,14 @@
 {
     "epoch": 10.0,
-    "eval_accuracy": 0.6065573770491803,
-    "eval_f1": 0.3511904761904762,
-    "eval_loss": 0.984711766242981,
-    "eval_runtime": 477.8963,
-    "eval_samples_per_second": 0.255,
-    "eval_steps_per_second": 0.033,
-    "total_flos": 9.455039533965312e+16,
-    "train_loss": 1.3333355903625488,
-    "train_runtime": 6360.4744,
-    "train_samples_per_second": 0.192,
-    "train_steps_per_second": 0.006
+    "eval_accuracy": 1.0,
+    "eval_f1": 1.0,
+    "eval_loss": 0.01199085172265768,
+    "eval_runtime": 31.5492,
+    "eval_samples_per_second": 0.222,
+    "eval_steps_per_second": 0.032,
+    "total_flos": 5424439273021440.0,
+    "train_loss": 0.1331296443939209,
+    "train_runtime": 406.2981,
+    "train_samples_per_second": 0.172,
+    "train_steps_per_second": 0.025
 }

eval_results.json

@@ -1,9 +1,9 @@
 {
     "epoch": 10.0,
-    "eval_accuracy": 0.6065573770491803,
-    "eval_f1": 0.3511904761904762,
-    "eval_loss": 0.984711766242981,
-    "eval_runtime": 477.8963,
-    "eval_samples_per_second": 0.255,
-    "eval_steps_per_second": 0.033
+    "eval_accuracy": 1.0,
+    "eval_f1": 1.0,
+    "eval_loss": 0.01199085172265768,
+    "eval_runtime": 31.5492,
+    "eval_samples_per_second": 0.222,
+    "eval_steps_per_second": 0.032
 }

test_results.json

@@ -0,0 +1,8 @@
+{
+    "epoch": 10.0,
+    "total_flos": 5424439273021440.0,
+    "train_loss": 0.1331296443939209,
+    "train_runtime": 406.2981,
+    "train_samples_per_second": 0.172,
+    "train_steps_per_second": 0.025
+}

trainer_state.json

@@ -3,26 +3,26 @@
   "best_model_checkpoint": null,
   "epoch": 10.0,
   "eval_steps": 1000,
-  "global_step": 40,
+  "global_step": 10,
   "is_hyper_param_search": false,
   "is_local_process_zero": true,
   "is_world_process_zero": true,
   "log_history": [
     {
       "epoch": 10.0,
-      "step": 40,
-      "total_flos": 9.455039533965312e+16,
-      "train_loss": 1.3333355903625488,
-      "train_runtime": 6360.4744,
-      "train_samples_per_second": 0.192,
-      "train_steps_per_second": 0.006
+      "step": 10,
+      "total_flos": 5424439273021440.0,
+      "train_loss": 0.1331296443939209,
+      "train_runtime": 406.2981,
+      "train_samples_per_second": 0.172,
+      "train_steps_per_second": 0.025
     }
   ],
   "logging_steps": 1000,
-  "max_steps": 40,
+  "max_steps": 10,
   "num_train_epochs": 10,
   "save_steps": 1000,
-  "total_flos": 9.455039533965312e+16,
+  "total_flos": 5424439273021440.0,
   "trial_name": null,
   "trial_params": null
 }