| import torch | |
| # --- MLM MASKING --- | |
| # --- MLM MASKING --- | |
| def mask_tokens(input_ids, vocab_size, mask_token_id, pad_token_id, mlm_prob=0.15 ): | |
| ''' | |
| TODO: Implement MLM masking | |
| Args: | |
| input_ids: Input IDs | |
| vocab_size: Vocabulary size | |
| mask_token_id: Mask token ID | |
| pad_token_id: Pad token ID | |
| mlm_prob: Probability of masking | |
| ''' | |
| pass | |
| def train_bert(model, dataloader, tokenizer, epochs=3, lr=5e-4, device='cuda'): | |
| ''' | |
| TODO: Implement training loop for BERT | |
| Args: | |
| model: BERT model | |
| dataloader: Data loader | |
| tokenizer: Tokenizer | |
| epochs: Number of epochs | |
| lr: Learning rate | |
| device: Device to run the model on | |
| ''' | |
| pass |