Update README.md

README.md

@@ -22,7 +22,7 @@ for a Speech Emotion Recognition (SER) task.
 
 The dataset used to fine-tune the original pre-trained model is
 the [RAVDESS dataset](https://zenodo.org/record/1188976#.YO6yI-gzaUk). This dataset provides 1440 samples of recordings
-from actors performing on 8 different emotions in English, which are:
+from actors performing on 5 different emotions in Bahasa Indonesia, which are:
 
 ```python
 emotions = ['angry', 'disgust', 'fear', 'happy', 'sad']
@@ -51,15 +51,15 @@ More information needed
 
 The following hyperparameters were used during training:
 
-- learning_rate: 0.0001
-- train_batch_size: 4
-- eval_batch_size: 4
+- learning_rate: 3e-5
+- train_batch_size: 32
+- eval_batch_size: 32
 - seed: 42
 - gradient_accumulation_steps: 2
-- total_train_batch_size: 8
+- total_train_batch_size: 10
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- num_epochs: 3
+- num_epochs: 10
 - mixed_precision_training: Native AMP
 
 ### Training results
@@ -84,11 +84,11 @@ The following hyperparameters were used during training:
 ## Citation
 
 ```bibtex
-@misc {enrique_hernández_calabrés_2024,
+@misc {alianur_rahman_2024,
 	author       = { {Alianur Rahman} },
-	title        = { wav2vec2-base-en-speech-emotion-recognition (Revision 17cf17c) },
+	title        = { wav2vec2-base-indonesian-speech-emotion-recognition (Revision 1fcfcf1) },
 	year         = 2024,
-	url          = { https://huggingface.co/alianurrahman/model }
+	url          = { https://huggingface.co/alianurrahman/wav2vec2-base-indonesian-speech-emotion-recognition }
 }
 ```