| # DistilBERT with 256k token embeddings | |
| This model was initialized with a word2vec token embedding matrix with 256k entries, but these token embeddings were updated during MLM. The word2vec was trained on 100GB data from C4, MSMARCO, News, Wikipedia, S2ORC, for 3 epochs. | |
| Then the model was trained on this dataset with MLM for 250k steps (batch size 64). The token embeddings were updated during MLM. | |
| For the same model but with frozen token embeddings while MLM training see: https://huggingface.co/vocab-transformers/distilbert-word2vec_256k-MLM_250k | |