Update README.md

README.md

@@ -1,99 +1,7 @@
 ---
 license: apache-2.0
-tags:
-- generated_from_trainer
-datasets:
-- imagefolder
-metrics:
-- accuracy
-- precision
-- recall
-- f1
-model-index:
-- name: emotion-dectect
-  results:
-  - task:
-      name: Image Classification
-      type: image-classification
-    dataset:
-      name: imagefolder
-      type: imagefolder
-      config: default
-      split: train
-      args: default
-    metrics:
-    - name: Accuracy
-      type: accuracy
-      value: 0.8807339449541285
-    - name: Precision
-      type: precision
-      value: 0.8768597487153273
-    - name: Recall
-      type: recall
-      value: 0.8807339449541285
-    - name: F1
-      type: f1
-      value: 0.8782945902988435
----
-
-<!-- This model card has been generated automatically according to the information the Trainer had access to. You
-should probably proofread and complete it, then remove this comment. -->
-
-# google-vit-base-patch16-224-cartoon-emotion-detection
-
-This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the imagefolder dataset.
-It achieves the following results on the evaluation set:
-- Loss: 0.3706
-- Accuracy: 0.8807
-- Precision: 0.8769
-- Recall: 0.8807
-- F1: 0.8783
-
-## Model description
-
-More information needed
-
-## Intended uses & limitations
-
-More information needed
-
-## Training and evaluation data
-
-More information needed
-
-## Training procedure
-
-### Training hyperparameters
-
-The following hyperparameters were used during training:
-- learning_rate: 0.00012
-- train_batch_size: 64
-- eval_batch_size: 64
-- seed: 42
-- gradient_accumulation_steps: 4
-- total_train_batch_size: 256
-- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
-- lr_scheduler_type: linear
-- lr_scheduler_warmup_ratio: 0.1
-- num_epochs: 10
-
-### Training results
-
-| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
-|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
-| No log        | 0.97  | 8    | 0.9902          | 0.5596   | 0.5506    | 0.5596 | 0.5360 |
-| 1.242         | 1.97  | 16   | 0.5157          | 0.8165   | 0.8195    | 0.8165 | 0.8132 |
-| 0.4438        | 2.97  | 24   | 0.3871          | 0.8440   | 0.8516    | 0.8440 | 0.8446 |
-| 0.1768        | 3.97  | 32   | 0.3531          | 0.8624   | 0.8653    | 0.8624 | 0.8585 |
-| 0.0661        | 4.97  | 40   | 0.3780          | 0.8716   | 0.8693    | 0.8716 | 0.8674 |
-| 0.0661        | 5.97  | 48   | 0.3747          | 0.8624   | 0.8649    | 0.8624 | 0.8632 |
-| 0.0375        | 6.97  | 56   | 0.3760          | 0.8991   | 0.8961    | 0.8991 | 0.8971 |
-| 0.0362        | 7.97  | 64   | 0.4092          | 0.8716   | 0.8684    | 0.8716 | 0.8681 |
-| 0.0322        | 8.97  | 72   | 0.3499          | 0.8899   | 0.8880    | 0.8899 | 0.8888 |
-| 0.029         | 9.97  | 80   | 0.3706          | 0.8807   | 0.8769    | 0.8807 | 0.8783 |
-
 
-### Framework versions
+#versions
 
 - Transformers 4.25.1
 - Pytorch 1.13.1+cu117