End of training

README.md

@@ -32,7 +32,7 @@ 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: 0.0156
+- Loss: 0.0338
 - Accuracy: 0.9884
 
 ## Model description

all_results.json

@@ -0,0 +1,13 @@
+{
+    "epoch": 2.94,
+    "eval_accuracy": 0.9884393063583815,
+    "eval_loss": 0.033755671232938766,
+    "eval_runtime": 3.2544,
+    "eval_samples_per_second": 53.158,
+    "eval_steps_per_second": 1.844,
+    "total_flos": 1.1374100559927706e+17,
+    "train_loss": 0.14240310589472452,
+    "train_runtime": 144.8377,
+    "train_samples_per_second": 32.146,
+    "train_steps_per_second": 0.249
+}

eval_results.json

@@ -0,0 +1,8 @@
+{
+    "epoch": 2.94,
+    "eval_accuracy": 0.9884393063583815,
+    "eval_loss": 0.033755671232938766,
+    "eval_runtime": 3.2544,
+    "eval_samples_per_second": 53.158,
+    "eval_steps_per_second": 1.844
+}

train_results.json

@@ -0,0 +1,8 @@
+{
+    "epoch": 2.94,
+    "total_flos": 1.1374100559927706e+17,
+    "train_loss": 0.14240310589472452,
+    "train_runtime": 144.8377,
+    "train_samples_per_second": 32.146,
+    "train_steps_per_second": 0.249
+}

trainer_state.json

@@ -0,0 +1,73 @@
+{
+  "best_metric": 0.9884393063583815,
+  "best_model_checkpoint": "swin-tiny-patch4-window7-224-finetuned-eurosat/checkpoint-12",
+  "epoch": 2.938775510204082,
+  "eval_steps": 500,
+  "global_step": 36,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
+    {
+      "epoch": 0.82,
+      "learning_rate": 4.0625000000000005e-05,
+      "loss": 0.4088,
+      "step": 10
+    },
+    {
+      "epoch": 0.98,
+      "eval_accuracy": 0.9884393063583815,
+      "eval_loss": 0.033755671232938766,
+      "eval_runtime": 3.1246,
+      "eval_samples_per_second": 55.367,
+      "eval_steps_per_second": 1.92,
+      "step": 12
+    },
+    {
+      "epoch": 1.63,
+      "learning_rate": 2.5e-05,
+      "loss": 0.0542,
+      "step": 20
+    },
+    {
+      "epoch": 1.96,
+      "eval_accuracy": 0.9884393063583815,
+      "eval_loss": 0.024054773151874542,
+      "eval_runtime": 3.8831,
+      "eval_samples_per_second": 44.552,
+      "eval_steps_per_second": 1.545,
+      "step": 24
+    },
+    {
+      "epoch": 2.45,
+      "learning_rate": 9.375000000000001e-06,
+      "loss": 0.0327,
+      "step": 30
+    },
+    {
+      "epoch": 2.94,
+      "eval_accuracy": 0.9884393063583815,
+      "eval_loss": 0.015622368082404137,
+      "eval_runtime": 4.1555,
+      "eval_samples_per_second": 41.632,
+      "eval_steps_per_second": 1.444,
+      "step": 36
+    },
+    {
+      "epoch": 2.94,
+      "step": 36,
+      "total_flos": 1.1374100559927706e+17,
+      "train_loss": 0.14240310589472452,
+      "train_runtime": 144.8377,
+      "train_samples_per_second": 32.146,
+      "train_steps_per_second": 0.249
+    }
+  ],
+  "logging_steps": 10,
+  "max_steps": 36,
+  "num_train_epochs": 3,
+  "save_steps": 500,
+  "total_flos": 1.1374100559927706e+17,
+  "trial_name": null,
+  "trial_params": null
+}