Update README.md

README.md

@@ -34,14 +34,4 @@ print(results)
 
 ### Training Data
 
-The model was trained on the [Twitter Financial News Sentiment](https://huggingface.co/datasets/zeroshot/twitter-financial-news-sentiment) dataset. The text data undergoes a comprehensive cleaning process (`data_preprocessing.py`) which includes:
-
-### Training Procedure
-
-The model was trained using the `transformers` library in PyTorch. The training script (`model_development.py`) includes the following features:
-
-- **Hyperparameter Optimization**: Optuna was used to find the best learning rate and batch size.
-- **Optimizer**: AdamW with a linear learning rate scheduler and warmup.
-- **Early Stopping**: Training stops if the validation accuracy does not improve for a set number of epochs.
-- **Mixed-Precision Training**: `torch.amp` was used for faster training.
-- **Gradient Accumulation**: To simulate a larger batch size.
+The model was trained on the [Twitter Financial News Sentiment](https://huggingface.co/datasets/zeroshot/twitter-financial-news-sentiment) dataset. The text data undergoes a comprehensive cleaning process (`data_preprocessing.py`) which includes: