Model save

README.md

@@ -20,11 +20,11 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [zkdeng/10-convnextv2-base-22k-384-finetuned-spiderTraining1000-1000](https://huggingface.co/zkdeng/10-convnextv2-base-22k-384-finetuned-spiderTraining1000-1000) on an unknown dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.0508
-- Accuracy: 0.9858
-- Precision: 0.9892
-- Recall: 0.9865
-- F1: 0.9878
+- Loss: 0.0184
+- Accuracy: 0.9929
+- Precision: 0.9955
+- Recall: 0.9910
+- F1: 0.9932
 
 ## Model description
 
@@ -44,12 +44,12 @@ More information needed
 
 The following hyperparameters were used during training:
 - learning_rate: 0.0005
-- train_batch_size: 8
-- eval_batch_size: 8
+- train_batch_size: 16
+- eval_batch_size: 16
 - seed: 42
 - distributed_type: multi-GPU
 - gradient_accumulation_steps: 4
-- total_train_batch_size: 32
+- total_train_batch_size: 64
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
 - lr_scheduler_warmup_ratio: 0.1
@@ -59,16 +59,16 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
-| 0.1997        | 1.0   | 281  | 0.2264          | 0.9281   | 0.9395    | 0.8869 | 0.9045 |
-| 0.17          | 2.0   | 563  | 0.1382          | 0.9565   | 0.8540    | 0.8266 | 0.8381 |
-| 0.21          | 3.0   | 845  | 0.1404          | 0.9583   | 0.9747    | 0.9064 | 0.9349 |
-| 0.1976        | 4.0   | 1127 | 0.0987          | 0.9689   | 0.9716    | 0.8917 | 0.9128 |
-| 0.178         | 5.0   | 1408 | 0.1219          | 0.9636   | 0.9393    | 0.9600 | 0.9472 |
-| 0.0659        | 6.0   | 1690 | 0.0804          | 0.9813   | 0.9815    | 0.9801 | 0.9807 |
-| 0.0917        | 7.0   | 1972 | 0.1062          | 0.9734   | 0.9765    | 0.9676 | 0.9716 |
-| 0.108         | 8.0   | 2254 | 0.0568          | 0.9849   | 0.9868    | 0.9794 | 0.9828 |
-| 0.1151        | 9.0   | 2535 | 0.0508          | 0.9858   | 0.9876    | 0.9863 | 0.9869 |
-| 0.049         | 9.97  | 2810 | 0.0508          | 0.9858   | 0.9892    | 0.9865 | 0.9878 |
+| 0.2684        | 1.0   | 141  | 0.1271          | 0.9503   | 0.9350    | 0.9199 | 0.9198 |
+| 0.1698        | 2.0   | 282  | 0.1668          | 0.9485   | 0.9229    | 0.9195 | 0.9123 |
+| 0.1538        | 3.0   | 423  | 0.0906          | 0.9645   | 0.9764    | 0.9365 | 0.9523 |
+| 0.153         | 4.0   | 564  | 0.0860          | 0.9707   | 0.9685    | 0.9451 | 0.9525 |
+| 0.0699        | 5.0   | 705  | 0.0528          | 0.9813   | 0.9830    | 0.9728 | 0.9776 |
+| 0.1107        | 6.0   | 846  | 0.0460          | 0.9831   | 0.9832    | 0.9879 | 0.9855 |
+| 0.0647        | 7.0   | 987  | 0.0319          | 0.9849   | 0.9905    | 0.9765 | 0.9829 |
+| 0.0461        | 8.0   | 1128 | 0.0350          | 0.9840   | 0.9866    | 0.9710 | 0.9776 |
+| 0.0371        | 9.0   | 1269 | 0.0198          | 0.9920   | 0.9952    | 0.9903 | 0.9927 |
+| 0.0496        | 10.0  | 1410 | 0.0184          | 0.9929   | 0.9955    | 0.9910 | 0.9932 |
 
 
 ### Framework versions