Model save

README.md

@@ -2,7 +2,6 @@
 license: apache-2.0
 base_model: google/vit-base-patch16-224-in21k
 tags:
-- image-classification
 - generated_from_trainer
 datasets:
 - imagefolder
@@ -15,7 +14,7 @@ model-index:
       name: Image Classification
       type: image-classification
     dataset:
-      name: Action_small_dataset
+      name: imagefolder
       type: imagefolder
       config: default
       split: train
@@ -23,7 +22,7 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.8785276073619632
+      value: 0.8711656441717791
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -31,10 +30,10 @@ should probably proofread and complete it, then remove this comment. -->
 
 # Action_all_10_class
 
-This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the Action_small_dataset dataset.
+This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the imagefolder dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.4146
-- Accuracy: 0.8785
+- Loss: 0.4745
+- Accuracy: 0.8712
 
 ## Model description
 
@@ -53,33 +52,47 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 0.0002
+- learning_rate: 0.0001
 - train_batch_size: 16
 - eval_batch_size: 8
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- num_epochs: 5
+- num_epochs: 10
 - mixed_precision_training: Native AMP
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 1.1239        | 0.35  | 100  | 0.9934          | 0.7117   |
-| 0.8878        | 0.69  | 200  | 0.7667          | 0.7706   |
-| 0.9037        | 1.04  | 300  | 0.6369          | 0.8098   |
-| 0.7307        | 1.38  | 400  | 0.5772          | 0.8319   |
-| 0.6624        | 1.73  | 500  | 0.6925          | 0.7718   |
-| 0.5781        | 2.08  | 600  | 0.5439          | 0.8405   |
-| 0.5537        | 2.42  | 700  | 0.5257          | 0.8331   |
-| 0.4112        | 2.77  | 800  | 0.4500          | 0.8564   |
-| 0.3263        | 3.11  | 900  | 0.4911          | 0.8417   |
-| 0.4592        | 3.46  | 1000 | 0.4551          | 0.8712   |
-| 0.3204        | 3.81  | 1100 | 0.4325          | 0.8724   |
-| 0.3268        | 4.15  | 1200 | 0.4529          | 0.8540   |
-| 0.4267        | 4.5   | 1300 | 0.4356          | 0.8724   |
-| 0.2886        | 4.84  | 1400 | 0.4146          | 0.8785   |
+| 1.1996        | 0.35  | 100  | 1.0635          | 0.7730   |
+| 1.0335        | 0.69  | 200  | 0.8392          | 0.7718   |
+| 0.6279        | 1.04  | 300  | 0.6463          | 0.8294   |
+| 0.8633        | 1.38  | 400  | 0.7172          | 0.7926   |
+| 0.5851        | 1.73  | 500  | 0.5858          | 0.8380   |
+| 0.5305        | 2.08  | 600  | 0.5780          | 0.8356   |
+| 0.5511        | 2.42  | 700  | 0.5313          | 0.8393   |
+| 0.4657        | 2.77  | 800  | 0.5443          | 0.8368   |
+| 0.3615        | 3.11  | 900  | 0.5038          | 0.8429   |
+| 0.5301        | 3.46  | 1000 | 0.5101          | 0.8503   |
+| 0.4108        | 3.81  | 1100 | 0.5212          | 0.8479   |
+| 0.4223        | 4.15  | 1200 | 0.5328          | 0.8429   |
+| 0.3877        | 4.5   | 1300 | 0.5815          | 0.8294   |
+| 0.3879        | 4.84  | 1400 | 0.5151          | 0.8503   |
+| 0.2797        | 5.19  | 1500 | 0.5160          | 0.8564   |
+| 0.2628        | 5.54  | 1600 | 0.4618          | 0.8699   |
+| 0.3404        | 5.88  | 1700 | 0.4903          | 0.8675   |
+| 0.3033        | 6.23  | 1800 | 0.4861          | 0.8663   |
+| 0.214         | 6.57  | 1900 | 0.4853          | 0.8687   |
+| 0.2763        | 6.92  | 2000 | 0.4705          | 0.8736   |
+| 0.3009        | 7.27  | 2100 | 0.4723          | 0.8626   |
+| 0.1543        | 7.61  | 2200 | 0.4983          | 0.8638   |
+| 0.2407        | 7.96  | 2300 | 0.4742          | 0.8650   |
+| 0.2679        | 8.3   | 2400 | 0.4935          | 0.8724   |
+| 0.1508        | 8.65  | 2500 | 0.4826          | 0.8675   |
+| 0.2129        | 9.0   | 2600 | 0.4981          | 0.8712   |
+| 0.1131        | 9.34  | 2700 | 0.4718          | 0.8712   |
+| 0.2144        | 9.69  | 2800 | 0.4745          | 0.8712   |
 
 
 ### Framework versions

model.safetensors

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 size 343248584

runs/Apr30_15-11-45_55836b80922a/events.out.tfevents.1714489905.55836b80922a.34.0

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training_args.bin

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