End of training

README.md

@@ -17,8 +17,8 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [facebook/convnextv2-tiny-1k-224](https://huggingface.co/facebook/convnextv2-tiny-1k-224) on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 1.5027
-- Accuracy: 0.3217
+- Loss: 1.5076
+- Accuracy: 0.3263
 
 ## Model description
 

all_results.json

@@ -0,0 +1,13 @@
+{
+    "epoch": 2.79,
+    "eval_accuracy": 0.32634032634032634,
+    "eval_loss": 1.5076048374176025,
+    "eval_runtime": 4.8909,
+    "eval_samples_per_second": 87.714,
+    "eval_steps_per_second": 2.862,
+    "total_flos": 9.58534533342167e+16,
+    "train_loss": 1.4979065895080566,
+    "train_runtime": 118.365,
+    "train_samples_per_second": 34.47,
+    "train_steps_per_second": 0.253
+}

eval_results.json

@@ -0,0 +1,8 @@
+{
+    "epoch": 2.79,
+    "eval_accuracy": 0.32634032634032634,
+    "eval_loss": 1.5076048374176025,
+    "eval_runtime": 4.8909,
+    "eval_samples_per_second": 87.714,
+    "eval_steps_per_second": 2.862
+}

train_results.json

@@ -0,0 +1,8 @@
+{
+    "epoch": 2.79,
+    "total_flos": 9.58534533342167e+16,
+    "train_loss": 1.4979065895080566,
+    "train_runtime": 118.365,
+    "train_samples_per_second": 34.47,
+    "train_steps_per_second": 0.253
+}

trainer_state.json

@@ -0,0 +1,73 @@
+{
+  "best_metric": 0.32634032634032634,
+  "best_model_checkpoint": "convnextv2-tiny-1k-224-for-pre_evaluation/checkpoint-21",
+  "epoch": 2.7906976744186047,
+  "eval_steps": 500,
+  "global_step": 30,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
+    {
+      "epoch": 0.93,
+      "learning_rate": 3.7037037037037037e-05,
+      "loss": 1.5431,
+      "step": 10
+    },
+    {
+      "epoch": 0.93,
+      "eval_accuracy": 0.3146853146853147,
+      "eval_loss": 1.5139713287353516,
+      "eval_runtime": 5.0638,
+      "eval_samples_per_second": 84.719,
+      "eval_steps_per_second": 2.765,
+      "step": 10
+    },
+    {
+      "epoch": 1.86,
+      "learning_rate": 1.8518518518518518e-05,
+      "loss": 1.4792,
+      "step": 20
+    },
+    {
+      "epoch": 1.95,
+      "eval_accuracy": 0.32634032634032634,
+      "eval_loss": 1.5076048374176025,
+      "eval_runtime": 6.2058,
+      "eval_samples_per_second": 69.129,
+      "eval_steps_per_second": 2.256,
+      "step": 21
+    },
+    {
+      "epoch": 2.79,
+      "learning_rate": 0.0,
+      "loss": 1.4714,
+      "step": 30
+    },
+    {
+      "epoch": 2.79,
+      "eval_accuracy": 0.32167832167832167,
+      "eval_loss": 1.5027328729629517,
+      "eval_runtime": 5.9368,
+      "eval_samples_per_second": 72.262,
+      "eval_steps_per_second": 2.358,
+      "step": 30
+    },
+    {
+      "epoch": 2.79,
+      "step": 30,
+      "total_flos": 9.58534533342167e+16,
+      "train_loss": 1.4979065895080566,
+      "train_runtime": 118.365,
+      "train_samples_per_second": 34.47,
+      "train_steps_per_second": 0.253
+    }
+  ],
+  "logging_steps": 10,
+  "max_steps": 30,
+  "num_train_epochs": 3,
+  "save_steps": 500,
+  "total_flos": 9.58534533342167e+16,
+  "trial_name": null,
+  "trial_params": null
+}