Model save

README.md

@@ -1,8 +1,7 @@
 ---
 license: apache-2.0
-base_model: Raihan004/Action_model
+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_class
+      name: imagefolder
       type: imagefolder
       config: default
       split: train
@@ -23,7 +22,7 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.8629173989455184
+      value: 0.8664323374340949
 ---
 
 <!-- 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_model
 
-This model is a fine-tuned version of [Raihan004/Action_model](https://huggingface.co/Raihan004/Action_model) on the action_class 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: 0.4790
-- Accuracy: 0.8629
+- Loss: 0.5153
+- Accuracy: 0.8664
 
 ## Model description
 
@@ -54,7 +53,7 @@ More information needed
 
 The following hyperparameters were used during training:
 - learning_rate: 0.0001
-- train_batch_size: 32
+- train_batch_size: 16
 - eval_batch_size: 8
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
@@ -66,19 +65,32 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 0.7766        | 0.75  | 100  | 0.6780          | 0.8225   |
-| 0.61          | 1.49  | 200  | 0.6279          | 0.8243   |
-| 0.4734        | 2.24  | 300  | 0.5593          | 0.8278   |
-| 0.5275        | 2.99  | 400  | 0.5148          | 0.8418   |
-| 0.3767        | 3.73  | 500  | 0.5129          | 0.8436   |
-| 0.3207        | 4.48  | 600  | 0.4966          | 0.8559   |
-| 0.3155        | 5.22  | 700  | 0.5251          | 0.8453   |
-| 0.2565        | 5.97  | 800  | 0.4790          | 0.8629   |
-| 0.2791        | 6.72  | 900  | 0.5111          | 0.8524   |
-| 0.1987        | 7.46  | 1000 | 0.5002          | 0.8453   |
-| 0.2083        | 8.21  | 1100 | 0.5034          | 0.8629   |
-| 0.2567        | 8.96  | 1200 | 0.4995          | 0.8576   |
-| 0.2127        | 9.7   | 1300 | 0.5034          | 0.8489   |
+| 1.2754        | 0.37  | 100  | 1.1163          | 0.7329   |
+| 0.9345        | 0.75  | 200  | 0.8296          | 0.7996   |
+| 0.8816        | 1.12  | 300  | 0.7156          | 0.8102   |
+| 0.7425        | 1.49  | 400  | 0.6529          | 0.8067   |
+| 0.6883        | 1.87  | 500  | 0.6079          | 0.8243   |
+| 0.5454        | 2.24  | 600  | 0.5605          | 0.8348   |
+| 0.5383        | 2.61  | 700  | 0.5571          | 0.8295   |
+| 0.5442        | 2.99  | 800  | 0.5864          | 0.8190   |
+| 0.3986        | 3.36  | 900  | 0.5632          | 0.8313   |
+| 0.3438        | 3.73  | 1000 | 0.5606          | 0.8366   |
+| 0.4345        | 4.1   | 1100 | 0.5354          | 0.8366   |
+| 0.4523        | 4.48  | 1200 | 0.4988          | 0.8576   |
+| 0.3162        | 4.85  | 1300 | 0.5099          | 0.8541   |
+| 0.3793        | 5.22  | 1400 | 0.5190          | 0.8436   |
+| 0.3228        | 5.6   | 1500 | 0.4589          | 0.8576   |
+| 0.1795        | 5.97  | 1600 | 0.5096          | 0.8489   |
+| 0.2626        | 6.34  | 1700 | 0.5403          | 0.8489   |
+| 0.3041        | 6.72  | 1800 | 0.4908          | 0.8489   |
+| 0.1831        | 7.09  | 1900 | 0.5721          | 0.8383   |
+| 0.2275        | 7.46  | 2000 | 0.5349          | 0.8313   |
+| 0.1762        | 7.84  | 2100 | 0.5204          | 0.8541   |
+| 0.2112        | 8.21  | 2200 | 0.5189          | 0.8629   |
+| 0.1242        | 8.58  | 2300 | 0.5377          | 0.8471   |
+| 0.1207        | 8.96  | 2400 | 0.5325          | 0.8559   |
+| 0.1806        | 9.33  | 2500 | 0.5150          | 0.8647   |
+| 0.1793        | 9.7   | 2600 | 0.5153          | 0.8664   |
 
 
 ### Framework versions

config.json

@@ -1,5 +1,5 @@
 {
-  "_name_or_path": "Raihan004/Action_model",
+  "_name_or_path": "google/vit-base-patch16-224-in21k",
   "architectures": [
     "ViTForImageClassification"
   ],

model.safetensors

@@ -1,3 +1,3 @@
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 size 343248584

runs/May09_07-16-20_361db62a36de/events.out.tfevents.1715258519.361db62a36de.34.0

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+size 70848

training_args.bin

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 size 4920