vuihocrnd/teacher-status-van-tiny-256

README.md

@@ -5,32 +5,9 @@ tags:
 - generated_from_trainer
 datasets:
 - imagefolder
-metrics:
-- accuracy
-- recall
-- precision
 model-index:
 - name: teacher-status-van-tiny-256
-  results:
-  - task:
-      name: Image Classification
-      type: image-classification
-    dataset:
-      name: imagefolder
-      type: imagefolder
-      config: default
-      split: train
-      args: default
-    metrics:
-    - name: Accuracy
-      type: accuracy
-      value: 0.949438202247191
-    - name: Recall
-      type: recall
-      value: 0.9514563106796117
-    - name: Precision
-      type: precision
-      value: 0.9607843137254902
+  results: []
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -40,11 +17,16 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [Visual-Attention-Network/van-tiny](https://huggingface.co/Visual-Attention-Network/van-tiny) on the imagefolder dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.1802
-- Accuracy: 0.9494
-- F1 Score: 0.9561
-- Recall: 0.9515
-- Precision: 0.9608
+- eval_loss: 0.2176
+- eval_accuracy: 0.9213
+- eval_f1_score: 0.9307
+- eval_recall: 0.9307
+- eval_precision: 0.9307
+- eval_runtime: 1.2169
+- eval_samples_per_second: 146.275
+- eval_steps_per_second: 4.931
+- epoch: 11.28
+- step: 141
 
 ## Model description
 
@@ -63,7 +45,7 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 5e-05
+- learning_rate: 0.0001
 - train_batch_size: 32
 - eval_batch_size: 32
 - seed: 42
@@ -72,16 +54,7 @@ The following hyperparameters were used during training:
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
 - lr_scheduler_warmup_ratio: 0.1
-- num_epochs: 3
-
-### Training results
-
-| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Score | Recall | Precision |
-|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:------:|:---------:|
-| 0.1511        | 0.96  | 12   | 0.1802          | 0.9494   | 0.9561   | 0.9515 | 0.9608    |
-| 0.2643        | 2.0   | 25   | 0.1674          | 0.9494   | 0.9557   | 0.9417 | 0.97      |
-| 0.3159        | 2.88  | 36   | 0.1692          | 0.9438   | 0.9510   | 0.9417 | 0.9604    |
-
+- num_epochs: 30
 
 ### Framework versions
 

all_results.json

@@ -1,16 +1,7 @@
 {
-    "epoch": 2.88,
-    "eval_accuracy": 0.949438202247191,
-    "eval_f1_score": 0.9560975609756097,
-    "eval_loss": 0.18015821278095245,
-    "eval_precision": 0.9607843137254902,
-    "eval_recall": 0.9514563106796117,
-    "eval_runtime": 1.0836,
-    "eval_samples_per_second": 164.273,
-    "eval_steps_per_second": 5.537,
-    "total_flos": 2.086337325249331e+16,
-    "train_loss": 0.2572544482019212,
-    "train_runtime": 70.0705,
-    "train_samples_per_second": 68.203,
-    "train_steps_per_second": 0.514
+    "eval_accuracy": 0.9213483146067416,
+    "eval_f1_score": 0.9306930693069307,
+    "eval_loss": 0.21757331490516663,
+    "eval_precision": 0.9306930693069307,
+    "eval_recall": 0.9306930693069307
 }

eval_results.json

@@ -1,11 +1,7 @@
 {
-    "epoch": 2.88,
-    "eval_accuracy": 0.949438202247191,
-    "eval_f1_score": 0.9560975609756097,
-    "eval_loss": 0.18015821278095245,
-    "eval_precision": 0.9607843137254902,
-    "eval_recall": 0.9514563106796117,
-    "eval_runtime": 1.0836,
-    "eval_samples_per_second": 164.273,
-    "eval_steps_per_second": 5.537
+    "eval_accuracy": 0.9213483146067416,
+    "eval_f1_score": 0.9306930693069307,
+    "eval_loss": 0.21757331490516663,
+    "eval_precision": 0.9306930693069307,
+    "eval_recall": 0.9306930693069307
 }

model.safetensors

@@ -1,3 +1,3 @@
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