End of training

README.md

@@ -1,6 +1,6 @@
 ---
 license: apache-2.0
-base_model: microsoft/swin-tiny-patch4-window7-224
+base_model: Lpdsc/swin-tiny-patch4-window7-224-finetuned-eurosat
 tags:
 - generated_from_trainer
 datasets:
@@ -22,7 +22,7 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.9152542372881356
+      value: 0.9661016949152542
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -30,10 +30,10 @@ should probably proofread and complete it, then remove this comment. -->
 
 # swin-tiny-patch4-window7-224-finetuned-eurosat
 
-This model is a fine-tuned version of [microsoft/swin-tiny-patch4-window7-224](https://huggingface.co/microsoft/swin-tiny-patch4-window7-224) on the imagefolder dataset.
+This model is a fine-tuned version of [Lpdsc/swin-tiny-patch4-window7-224-finetuned-eurosat](https://huggingface.co/Lpdsc/swin-tiny-patch4-window7-224-finetuned-eurosat) on the imagefolder dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.2906
-- Accuracy: 0.9153
+- Loss: 0.1318
+- Accuracy: 0.9661
 
 ## Model description
 
@@ -67,14 +67,14 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| No log        | 0.94  | 4    | 0.4790          | 0.7458   |
-| No log        | 1.88  | 8    | 0.3245          | 0.8644   |
-| 0.4186        | 2.82  | 12   | 0.2906          | 0.9153   |
+| No log        | 0.94  | 4    | 0.1318          | 0.9661   |
+| No log        | 1.88  | 8    | 0.0986          | 0.9661   |
+| 0.1962        | 2.82  | 12   | 0.0766          | 0.9661   |
 
 
 ### Framework versions
 
 - Transformers 4.38.2
-- Pytorch 2.1.0+cu121
+- Pytorch 2.2.1+cu121
 - Datasets 2.18.0
 - Tokenizers 0.15.2

all_results.json

@@ -1,13 +1,13 @@
 {
     "epoch": 2.82,
-    "eval_accuracy": 0.9152542372881356,
-    "eval_loss": 0.29061949253082275,
-    "eval_runtime": 3.4295,
-    "eval_samples_per_second": 17.204,
-    "eval_steps_per_second": 0.583,
+    "eval_accuracy": 0.9661016949152542,
+    "eval_loss": 0.13184800744056702,
+    "eval_runtime": 5.0738,
+    "eval_samples_per_second": 11.628,
+    "eval_steps_per_second": 0.394,
     "total_flos": 3.7283983478784e+16,
-    "train_loss": 0.3904288361469905,
-    "train_runtime": 118.5728,
-    "train_samples_per_second": 13.308,
-    "train_steps_per_second": 0.101
+    "train_loss": 0.18169777592023215,
+    "train_runtime": 137.0663,
+    "train_samples_per_second": 11.513,
+    "train_steps_per_second": 0.088
 }

config.json

@@ -1,5 +1,5 @@
 {
-  "_name_or_path": "microsoft/swin-tiny-patch4-window7-224",
+  "_name_or_path": "Lpdsc/swin-tiny-patch4-window7-224-finetuned-eurosat",
   "architectures": [
     "SwinForImageClassification"
   ],

eval_results.json

@@ -1,8 +1,8 @@
 {
     "epoch": 2.82,
-    "eval_accuracy": 0.9152542372881356,
-    "eval_loss": 0.29061949253082275,
-    "eval_runtime": 3.4295,
-    "eval_samples_per_second": 17.204,
-    "eval_steps_per_second": 0.583
+    "eval_accuracy": 0.9661016949152542,
+    "eval_loss": 0.13184800744056702,
+    "eval_runtime": 5.0738,
+    "eval_samples_per_second": 11.628,
+    "eval_steps_per_second": 0.394
 }

model.safetensors

@@ -1,3 +1,3 @@
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 size 110342832

runs/Mar14_14-37-33_ec8b9ba97c80/events.out.tfevents.1710427054.ec8b9ba97c80.4846.0

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runs/Mar14_14-37-33_ec8b9ba97c80/events.out.tfevents.1710427197.ec8b9ba97c80.4846.1

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train_results.json

@@ -1,8 +1,8 @@
 {
     "epoch": 2.82,
     "total_flos": 3.7283983478784e+16,
-    "train_loss": 0.3904288361469905,
-    "train_runtime": 118.5728,
-    "train_samples_per_second": 13.308,
-    "train_steps_per_second": 0.101
+    "train_loss": 0.18169777592023215,
+    "train_runtime": 137.0663,
+    "train_samples_per_second": 11.513,
+    "train_steps_per_second": 0.088
 }

trainer_state.json

@@ -1,6 +1,6 @@
 {
-  "best_metric": 0.9152542372881356,
-  "best_model_checkpoint": "swin-tiny-patch4-window7-224-finetuned-eurosat/checkpoint-12",
+  "best_metric": 0.9661016949152542,
+  "best_model_checkpoint": "swin-tiny-patch4-window7-224-finetuned-eurosat/checkpoint-4",
   "epoch": 2.8235294117647056,
   "eval_steps": 500,
   "global_step": 12,
@@ -10,46 +10,46 @@
   "log_history": [
     {
       "epoch": 0.94,
-      "eval_accuracy": 0.7457627118644068,
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-      "eval_runtime": 3.3638,
-      "eval_samples_per_second": 17.54,
-      "eval_steps_per_second": 0.595,
+      "eval_accuracy": 0.9661016949152542,
+      "eval_loss": 0.13184800744056702,
+      "eval_runtime": 3.5686,
+      "eval_samples_per_second": 16.533,
+      "eval_steps_per_second": 0.56,
       "step": 4
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     {
       "epoch": 1.88,
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-      "eval_loss": 0.32449179887771606,
-      "eval_runtime": 3.4489,
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+      "eval_accuracy": 0.9661016949152542,
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+      "eval_runtime": 3.4474,
+      "eval_samples_per_second": 17.114,
       "eval_steps_per_second": 0.58,
       "step": 8
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     {
       "epoch": 2.35,
-      "grad_norm": 4.969060897827148,
+      "grad_norm": 5.057217597961426,
       "learning_rate": 1e-05,
-      "loss": 0.4186,
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       "step": 10
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     {
       "epoch": 2.82,
-      "eval_accuracy": 0.9152542372881356,
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       "step": 12
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     {
       "epoch": 2.82,
       "step": 12,
       "total_flos": 3.7283983478784e+16,
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-      "train_runtime": 118.5728,
-      "train_samples_per_second": 13.308,
-      "train_steps_per_second": 0.101
+      "train_loss": 0.18169777592023215,
+      "train_runtime": 137.0663,
+      "train_samples_per_second": 11.513,
+      "train_steps_per_second": 0.088
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   "logging_steps": 10,

training_args.bin

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