End of training

README.md

@@ -5,24 +5,9 @@ tags:
 - generated_from_trainer
 datasets:
 - imagefolder
-metrics:
-- accuracy
 model-index:
 - name: image_classification
-  results:
-  - task:
-      name: Image Classification
-      type: image-classification
-    dataset:
-      name: imagefolder
-      type: imagefolder
-      config: en-US
-      split: train
-      args: en-US
-    metrics:
-    - name: Accuracy
-      type: accuracy
-      value: 0.525
+  results: []
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -32,8 +17,12 @@ should probably proofread and complete it, then remove this comment. -->
 
 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: 1.9905
-- Accuracy: 0.525
+- eval_loss: 2.0725
+- eval_accuracy: 0.1437
+- eval_runtime: 142.7817
+- eval_samples_per_second: 1.121
+- eval_steps_per_second: 0.07
+- step: 0
 
 ## Model description
 
@@ -52,7 +41,7 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 0.0001
+- learning_rate: 5e-06
 - train_batch_size: 16
 - eval_batch_size: 16
 - seed: 42
@@ -60,62 +49,6 @@ The following hyperparameters were used during training:
 - lr_scheduler_type: linear
 - num_epochs: 50
 
-### Training results
-
-| Training Loss | Epoch | Step | Validation Loss | Accuracy |
-|:-------------:|:-----:|:----:|:---------------:|:--------:|
-| No log        | 1.0   | 40   | 1.7409          | 0.2875   |
-| No log        | 2.0   | 80   | 1.5124          | 0.4375   |
-| No log        | 3.0   | 120  | 1.4255          | 0.4437   |
-| No log        | 4.0   | 160  | 1.4154          | 0.425    |
-| No log        | 5.0   | 200  | 1.2886          | 0.4625   |
-| No log        | 6.0   | 240  | 1.2963          | 0.5125   |
-| No log        | 7.0   | 280  | 1.3139          | 0.55     |
-| No log        | 8.0   | 320  | 1.2976          | 0.5312   |
-| No log        | 9.0   | 360  | 1.4368          | 0.5062   |
-| No log        | 10.0  | 400  | 1.4022          | 0.5062   |
-| No log        | 11.0  | 440  | 1.2853          | 0.55     |
-| No log        | 12.0  | 480  | 1.3265          | 0.5563   |
-| 0.8831        | 13.0  | 520  | 1.3894          | 0.55     |
-| 0.8831        | 14.0  | 560  | 1.4465          | 0.5312   |
-| 0.8831        | 15.0  | 600  | 1.7185          | 0.475    |
-| 0.8831        | 16.0  | 640  | 1.7408          | 0.4875   |
-| 0.8831        | 17.0  | 680  | 1.5199          | 0.5437   |
-| 0.8831        | 18.0  | 720  | 1.7238          | 0.525    |
-| 0.8831        | 19.0  | 760  | 1.8348          | 0.4875   |
-| 0.8831        | 20.0  | 800  | 1.6278          | 0.5125   |
-| 0.8831        | 21.0  | 840  | 1.7539          | 0.5      |
-| 0.8831        | 22.0  | 880  | 1.9007          | 0.4938   |
-| 0.8831        | 23.0  | 920  | 1.6903          | 0.5375   |
-| 0.8831        | 24.0  | 960  | 1.7954          | 0.5062   |
-| 0.2214        | 25.0  | 1000 | 1.7070          | 0.575    |
-| 0.2214        | 26.0  | 1040 | 1.6764          | 0.5625   |
-| 0.2214        | 27.0  | 1080 | 1.8590          | 0.5188   |
-| 0.2214        | 28.0  | 1120 | 1.7531          | 0.5188   |
-| 0.2214        | 29.0  | 1160 | 1.5238          | 0.5875   |
-| 0.2214        | 30.0  | 1200 | 1.6463          | 0.6      |
-| 0.2214        | 31.0  | 1240 | 1.7955          | 0.5563   |
-| 0.2214        | 32.0  | 1280 | 1.9920          | 0.5      |
-| 0.2214        | 33.0  | 1320 | 1.8826          | 0.55     |
-| 0.2214        | 34.0  | 1360 | 2.0573          | 0.5      |
-| 0.2214        | 35.0  | 1400 | 1.8438          | 0.5312   |
-| 0.2214        | 36.0  | 1440 | 1.9004          | 0.5312   |
-| 0.2214        | 37.0  | 1480 | 1.8215          | 0.5437   |
-| 0.1479        | 38.0  | 1520 | 2.0467          | 0.5437   |
-| 0.1479        | 39.0  | 1560 | 1.8564          | 0.5687   |
-| 0.1479        | 40.0  | 1600 | 1.8381          | 0.5687   |
-| 0.1479        | 41.0  | 1640 | 1.8110          | 0.5687   |
-| 0.1479        | 42.0  | 1680 | 2.0587          | 0.5375   |
-| 0.1479        | 43.0  | 1720 | 1.9597          | 0.5687   |
-| 0.1479        | 44.0  | 1760 | 1.9199          | 0.5687   |
-| 0.1479        | 45.0  | 1800 | 1.8714          | 0.5312   |
-| 0.1479        | 46.0  | 1840 | 1.9463          | 0.575    |
-| 0.1479        | 47.0  | 1880 | 2.0449          | 0.5312   |
-| 0.1479        | 48.0  | 1920 | 1.9172          | 0.525    |
-| 0.1479        | 49.0  | 1960 | 1.9153          | 0.55     |
-| 0.0946        | 50.0  | 2000 | 1.9905          | 0.525    |
-
-
 ### Framework versions
 
 - Transformers 4.33.2

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