Upload ./README.md with huggingface_hub

README.md

@@ -56,9 +56,9 @@ ProgressGym-HistLlama3-70B-C020-instruct is one of the **36 historical language
 
 ... where training results can be found in `all_results.json`, `trainer_log.jsonl`, and `training_loss.png` of the pretrain model.
 
-Note that the training data volume for the continued pretraining stage is capped at 300MB. When the corresponding century's corpus exceeds this volume, the training data is randomly sampled to fit the volume.
+Note that the training data volume for the continued pretraining stage is capped at 3GB. When the corresponding century's corpus exceeds this volume, the training data is randomly sampled to fit the volume.
 
-**ProgressGym-HistLlama3-70B-C020-instruct is an instruction-tuned language model.** It is tuned on [ProgressGym-TimelessQA](https://huggingface.co/datasets/PKU-Alignment/ProgressGym-TimelessQA), using the following hyperparameters:
+**ProgressGym-HistLlama3-70B-C020-instruct is an instruction-tuned language model.** It is tuned on [ProgressGym-TimelessQA](https://huggingface.co/datasets/PKU-Alignment/ProgressGym-TimelessQA), using the following hyperparameters. Note, however, that the snapshot at training step 10 is used for the final model, to minimize erosion of the value tendencies learned during continued pretraining; we qualitatively observe that this snapshot still possesses strong instruction-following capabilities.
 - learning_rate: 3e-06
 - train_batch_size: 2
 - eval_batch_size: 4
@@ -83,6 +83,7 @@ Note that the training data volume for the continued pretraining stage is capped
 - **[Leaderboard & Interactive Playground]** [PKU-Alignment/ProgressGym-LeaderBoard](https://huggingface.co/spaces/PKU-Alignment/ProgressGym-LeaderBoard)
 - **[Huggingface Data & Model Collection]** [PKU-Alignment/ProgressGym](https://huggingface.co/collections/PKU-Alignment/progressgym-666735fcf3e4efa276226eaa)
 - **[Github Codebase]** [PKU-Alignment/ProgressGym](https://github.com/PKU-Alignment/ProgressGym)
+- **[Documentation]** [ProgressGym Documentation](https://pku-alignment.github.io/ProgressGym/)
 - **[PyPI Package]** *(coming soon - [stay tuned](https://forms.gle/1TWFLL4ZCLeYTD5N6)!)*
 
 ## Citation