SAWiT Model Training
Overview
This project is a machine learning model built for the SAWiT task. The model is trained on tokenized text data and is designed to solve [state the problem the model is solving].
Dataset
The dataset used for training is a tokenized dataset, which has been preprocessed and saved in the tokenized_data directory. It contains the following files:
train.arrowvalidation.arrowtest.arrow
These files are in Arrow format and were saved using the Hugging Face datasets library.
Model Details
The model architecture is based on [mention model type, e.g., BERT, GPT, LSTM, etc.], and was trained using the [framework, e.g., TensorFlow or PyTorch]. The model performs [state task, e.g., classification, prediction, etc.].
Training
To train the model, follow these steps:
- Ensure that the dataset has been preprocessed and saved to the
tokenized_data folder.
- Run the training script:
