Model save

README.md

@@ -4,7 +4,7 @@ base_model: google/vit-base-patch16-224-in21k
 tags:
 - generated_from_trainer
 datasets:
-- imagefolder
+- image_folder
 metrics:
 - accuracy
 model-index:
@@ -14,15 +14,15 @@ model-index:
       name: Image Classification
       type: image-classification
     dataset:
-      name: imagefolder
-      type: imagefolder
+      name: image_folder
+      type: image_folder
       config: default
       split: train
       args: default
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.3103448275862069
+      value: 0.9925
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -30,10 +30,10 @@ should probably proofread and complete it, then remove this comment. -->
 
 # vit-base-patch16-224-in21k-finetune
 
-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.
+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 image_folder dataset.
 It achieves the following results on the evaluation set:
-- Loss: 1.5597
-- Accuracy: 0.3103
+- Loss: 0.8622
+- Accuracy: 0.9925
 
 ## Model description
 
@@ -52,7 +52,7 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 2e-05
+- learning_rate: 5e-05
 - train_batch_size: 64
 - eval_batch_size: 64
 - seed: 42
@@ -61,22 +61,20 @@ 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: 5
+- num_epochs: 3
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| No log        | 0.92  | 3    | 1.5697          | 0.2874   |
-| No log        | 1.85  | 6    | 1.5657          | 0.2759   |
-| No log        | 2.77  | 9    | 1.5628          | 0.2759   |
-| 1.5842        | 4.0   | 13   | 1.5602          | 0.3103   |
-| 1.5842        | 4.62  | 15   | 1.5597          | 0.3103   |
+| 1.928         | 0.98  | 14   | 1.4445          | 0.9625   |
+| 1.473         | 1.96  | 28   | 0.9995          | 0.985    |
+| 0.957         | 2.95  | 42   | 0.8622          | 0.9925   |
 
 
 ### Framework versions
 
-- Transformers 4.39.3
+- Transformers 4.38.1
 - Pytorch 2.1.2
-- Datasets 2.18.0
+- Datasets 2.1.0
 - Tokenizers 0.15.2

runs/May07_05-38-56_7ee871a99c58/events.out.tfevents.1715060354.7ee871a99c58.34.0

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
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-size 6707
+oid sha256:e4826252f949056ebbabd88e5097bd49f580f199a6a0d6cdec5981394c91debd
+size 7055