End of training

README.md

@@ -22,7 +22,7 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.9736842105263158
+      value: 0.9868421052631579
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -32,8 +32,8 @@ should probably proofread and complete it, then remove this comment. -->
 
 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.
 It achieves the following results on the evaluation set:
-- Loss: 0.0741
-- Accuracy: 0.9737
+- Loss: 0.0703
+- Accuracy: 0.9868
 
 ## Model description
 

all_results.json

@@ -0,0 +1,12 @@
+{
+    "epoch": 3.95,
+    "eval_accuracy": 0.9868421052631579,
+    "eval_loss": 0.07025326788425446,
+    "eval_runtime": 16.0481,
+    "eval_samples_per_second": 4.736,
+    "eval_steps_per_second": 0.623,
+    "train_loss": 0.41509221210366204,
+    "train_runtime": 1289.7394,
+    "train_samples_per_second": 2.1,
+    "train_steps_per_second": 0.065
+}

eval_results.json

@@ -0,0 +1,8 @@
+{
+    "epoch": 3.95,
+    "eval_accuracy": 0.9868421052631579,
+    "eval_loss": 0.07025326788425446,
+    "eval_runtime": 16.0481,
+    "eval_samples_per_second": 4.736,
+    "eval_steps_per_second": 0.623
+}

train_results.json

@@ -0,0 +1,7 @@
+{
+    "epoch": 3.95,
+    "train_loss": 0.41509221210366204,
+    "train_runtime": 1289.7394,
+    "train_samples_per_second": 2.1,
+    "train_steps_per_second": 0.065
+}

trainer_state.json

@@ -0,0 +1,112 @@
+{
+  "best_metric": 0.9868421052631579,
+  "best_model_checkpoint": "swin-tiny-patch4-window7-224-finetuned-herbify_plants\\checkpoint-63",
+  "epoch": 3.9529411764705884,
+  "eval_steps": 500,
+  "global_step": 84,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
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+      "epoch": 0.47,
+      "learning_rate": 4.933333333333334e-05,
+      "loss": 1.507,
+      "step": 10
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+    {
+      "epoch": 0.94,
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+      "loss": 0.7849,
+      "step": 20
+    },
+    {
+      "epoch": 0.99,
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+      "eval_runtime": 16.1772,
+      "eval_samples_per_second": 4.698,
+      "eval_steps_per_second": 0.618,
+      "step": 21
+    },
+    {
+      "epoch": 1.41,
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+    {
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+    },
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+      "epoch": 1.98,
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+      "eval_loss": 0.1294979751110077,
+      "eval_runtime": 14.2688,
+      "eval_samples_per_second": 5.326,
+      "eval_steps_per_second": 0.701,
+      "step": 42
+    },
+    {
+      "epoch": 2.35,
+      "learning_rate": 2.2666666666666668e-05,
+      "loss": 0.181,
+      "step": 50
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+    {
+      "epoch": 2.82,
+      "learning_rate": 1.6000000000000003e-05,
+      "loss": 0.1387,
+      "step": 60
+    },
+    {
+      "epoch": 2.96,
+      "eval_accuracy": 0.9868421052631579,
+      "eval_loss": 0.07025326788425446,
+      "eval_runtime": 14.5008,
+      "eval_samples_per_second": 5.241,
+      "eval_steps_per_second": 0.69,
+      "step": 63
+    },
+    {
+      "epoch": 3.29,
+      "learning_rate": 9.333333333333334e-06,
+      "loss": 0.1162,
+      "step": 70
+    },
+    {
+      "epoch": 3.76,
+      "learning_rate": 2.666666666666667e-06,
+      "loss": 0.1039,
+      "step": 80
+    },
+    {
+      "epoch": 3.95,
+      "eval_accuracy": 0.9736842105263158,
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+      "eval_runtime": 14.5312,
+      "eval_samples_per_second": 5.23,
+      "eval_steps_per_second": 0.688,
+      "step": 84
+    },
+    {
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+      "step": 84,
+      "total_flos": 6.659477648048333e+16,
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+    }
+  ],
+  "logging_steps": 10,
+  "max_steps": 84,
+  "num_train_epochs": 4,
+  "save_steps": 500,
+  "total_flos": 6.659477648048333e+16,
+  "trial_name": null,
+  "trial_params": null
+}