Update README.md

README.md

@@ -1,47 +1,43 @@
 ---
 license: apache-2.0
-tags:
-- generated_from_keras_callback
 model-index:
 - name: vit-base-vocalsound-logmel
   results: []
 ---
 
-<!-- This model card has been generated automatically according to the information Keras had access to. You should
-probably proofread and complete it, then remove this comment. -->
-
 # vit-base-vocalsound-logmel
 
-This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on an unknown dataset.
+This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on [VocalSound](https://github.com/YuanGongND/vocalsound) dataset.
 It achieves the following results on the evaluation set:
 
-
-## Model description
-
-More information needed
-
-## Intended uses & limitations
-
-More information needed
+- accuracy: 88.8
+- precision (micro): 91.3
+- recall (micro): 87.1
+- f1 score (micro): 89.1
+- f1 score (macro): 89.1
 
 ## Training and evaluation data
 
-More information needed
+Training: VocalSound training split (#samples = 15570)
 
-## Training procedure
+Evaluation: VocalSound test split(#samples = 3594)
 
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- optimizer: None
+- optimizer: AdamW
+  - weight_decay: 0
+  - learning_rate: 5e-5
+- batch_size: 32
 - training_precision: float32
 
-### Training results
-
+### Preprocessing
 
+Differently from [vit-base-vocalsound](https://huggingface.co/andrei-saceleanu/vit-base-vocalsound), the log-melspectrogram is used(log was applied as an addition) and the preprocessor normalization
+step uses VocalSound statistics(i.e. mean and std) instead of the default IMAGENET ones.
 
 ### Framework versions
 
 - Transformers 4.27.4
 - TensorFlow 2.12.0
-- Tokenizers 0.13.3
+- Tokenizers 0.13.3