trantridat/SwinV2Base_lora r64 alpha16 dropout0.05 batchsize64 lr0.001

README.md

@@ -22,11 +22,11 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [microsoft/swinv2-base-patch4-window12-192-22k](https://huggingface.co/microsoft/swinv2-base-patch4-window12-192-22k) on the imagefolder dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.4540
-- Accuracy: 0.9098
-- Precision: 0.9091
-- Recall: 0.9098
-- F1: 0.9091
+- Loss: 0.4329
+- Accuracy: 0.9160
+- Precision: 0.9157
+- Recall: 0.9160
+- F1: 0.9156
 
 ## Model description
 

all_results.json

@@ -0,0 +1,16 @@
+{
+    "epoch": 99.2,
+    "eval_accuracy": 0.9160090191657272,
+    "eval_f1": 0.9156304372279399,
+    "eval_loss": 0.4329167902469635,
+    "eval_precision": 0.9156707582414666,
+    "eval_recall": 0.9160090191657272,
+    "eval_runtime": 35.1992,
+    "eval_samples_per_second": 50.399,
+    "eval_steps_per_second": 0.795,
+    "total_flos": 9.4522774317222e+19,
+    "train_loss": 0.2388173005080992,
+    "train_runtime": 58791.9316,
+    "train_samples_per_second": 27.141,
+    "train_steps_per_second": 0.105
+}

eval_results.json

@@ -0,0 +1,11 @@
+{
+    "epoch": 99.2,
+    "eval_accuracy": 0.9160090191657272,
+    "eval_f1": 0.9156304372279399,
+    "eval_loss": 0.4329167902469635,
+    "eval_precision": 0.9156707582414666,
+    "eval_recall": 0.9160090191657272,
+    "eval_runtime": 35.1992,
+    "eval_samples_per_second": 50.399,
+    "eval_steps_per_second": 0.795
+}

train_results.json

@@ -0,0 +1,8 @@
+{
+    "epoch": 99.2,
+    "total_flos": 9.4522774317222e+19,
+    "train_loss": 0.2388173005080992,
+    "train_runtime": 58791.9316,
+    "train_samples_per_second": 27.141,
+    "train_steps_per_second": 0.105
+}