Model save

README.md

@@ -2,28 +2,12 @@
 license: apache-2.0
 base_model: google/vit-base-patch16-224-in21k
 tags:
-- image-classification
 - generated_from_trainer
-datasets:
-- imagefolder
 metrics:
 - accuracy
 model-index:
 - name: Action_all_10_class
-  results:
-  - task:
-      name: Image Classification
-      type: image-classification
-    dataset:
-      name: Action_small_dataset
-      type: imagefolder
-      config: default
-      split: train
-      args: default
-    metrics:
-    - name: Accuracy
-      type: accuracy
-      value: 0.8646723646723646
+  results: []
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -31,10 +15,10 @@ 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 an unknown dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.5056
-- Accuracy: 0.8647
+- Loss: 0.4417
+- Accuracy: 0.8604
 
 ## Model description
 
@@ -59,50 +43,25 @@ The following hyperparameters were used during training:
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- num_epochs: 15
+- num_epochs: 5
 - mixed_precision_training: Native AMP
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 1.1504        | 0.4   | 100  | 0.8748          | 0.7778   |
-| 0.944         | 0.8   | 200  | 0.8147          | 0.7550   |
-| 0.9096        | 1.2   | 300  | 0.7891          | 0.7507   |
-| 0.7847        | 1.61  | 400  | 0.7498          | 0.7749   |
-| 0.7296        | 2.01  | 500  | 0.6465          | 0.8034   |
-| 0.7107        | 2.41  | 600  | 0.7201          | 0.7550   |
-| 0.5229        | 2.81  | 700  | 0.7578          | 0.7521   |
-| 0.4698        | 3.21  | 800  | 0.6027          | 0.8120   |
-| 0.4846        | 3.61  | 900  | 0.7316          | 0.7877   |
-| 0.5676        | 4.02  | 1000 | 0.6542          | 0.7949   |
-| 0.4784        | 4.42  | 1100 | 0.6611          | 0.7991   |
-| 0.411         | 4.82  | 1200 | 0.5830          | 0.8077   |
-| 0.4021        | 5.22  | 1300 | 0.5220          | 0.8447   |
-| 0.6442        | 5.62  | 1400 | 0.7222          | 0.7849   |
-| 0.4539        | 6.02  | 1500 | 0.5616          | 0.8348   |
-| 0.4256        | 6.43  | 1600 | 0.6622          | 0.8020   |
-| 0.2839        | 6.83  | 1700 | 0.6048          | 0.8262   |
-| 0.4236        | 7.23  | 1800 | 0.5745          | 0.8262   |
-| 0.3371        | 7.63  | 1900 | 0.5558          | 0.8447   |
-| 0.2564        | 8.03  | 2000 | 0.5993          | 0.8376   |
-| 0.2802        | 8.43  | 2100 | 0.5202          | 0.8590   |
-| 0.2938        | 8.84  | 2200 | 0.6191          | 0.8177   |
-| 0.2777        | 9.24  | 2300 | 0.5119          | 0.8504   |
-| 0.1851        | 9.64  | 2400 | 0.5541          | 0.8547   |
-| 0.2274        | 10.04 | 2500 | 0.5599          | 0.8433   |
-| 0.3051        | 10.44 | 2600 | 0.5281          | 0.8504   |
-| 0.2368        | 10.84 | 2700 | 0.5056          | 0.8647   |
-| 0.2029        | 11.24 | 2800 | 0.5582          | 0.8390   |
-| 0.1971        | 11.65 | 2900 | 0.5440          | 0.8433   |
-| 0.2014        | 12.05 | 3000 | 0.5088          | 0.8618   |
-| 0.1458        | 12.45 | 3100 | 0.5539          | 0.8618   |
-| 0.139         | 12.85 | 3200 | 0.5866          | 0.8433   |
-| 0.2202        | 13.25 | 3300 | 0.5248          | 0.8590   |
-| 0.1421        | 13.65 | 3400 | 0.5548          | 0.8476   |
-| 0.211         | 14.06 | 3500 | 0.5502          | 0.8490   |
-| 0.2106        | 14.46 | 3600 | 0.5413          | 0.8504   |
-| 0.1716        | 14.86 | 3700 | 0.5398          | 0.8462   |
+| 1.0772        | 0.4   | 100  | 1.0525          | 0.6738   |
+| 0.9054        | 0.8   | 200  | 0.7350          | 0.8006   |
+| 0.9093        | 1.2   | 300  | 0.6519          | 0.8162   |
+| 0.6264        | 1.61  | 400  | 0.6052          | 0.8105   |
+| 0.9279        | 2.01  | 500  | 0.6442          | 0.7934   |
+| 0.5023        | 2.41  | 600  | 0.5365          | 0.8262   |
+| 0.4644        | 2.81  | 700  | 0.5505          | 0.8305   |
+| 0.4217        | 3.21  | 800  | 0.5024          | 0.8433   |
+| 0.4447        | 3.61  | 900  | 0.4700          | 0.8533   |
+| 0.4073        | 4.02  | 1000 | 0.4605          | 0.8632   |
+| 0.2679        | 4.42  | 1100 | 0.4259          | 0.8661   |
+| 0.262         | 4.82  | 1200 | 0.4417          | 0.8604   |
 
 
 ### Framework versions

model.safetensors

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runs/Nov19_09-32-04_09d27efa0afa/events.out.tfevents.1700386331.09d27efa0afa.31695.0

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+size 28930

training_args.bin

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