Update README.md

README.md

@@ -9,16 +9,20 @@ about 1800 training samples _up to_ 4k tokens length. A 2-pass training procedur
 finetuning on about 6800 stories within 4k tokens length and the second pass is LimaRP with changes introducing more effective
 control on response length.
 
-**Due to software limitations, finetuning didn't take advantage yet of the Sliding Window Attention (SWA) which would have allowed
-to use longer conversations in the training data. Thus, this version of LimaRP should be considered an _initial finetuning attempt_ and
-will be updated in the future.**
-
 For more details about LimaRP, see the model page for the [previously released v2 version for Llama-2](https://huggingface.co/lemonilia/limarp-llama2-v2).
 Most details written there apply for this version as well. Generally speaking, LimaRP is a longform-oriented, novel-style
 roleplaying chat model intended to replicate the experience of 1-on-1 roleplay on Internet forums. Short-form,
 IRC/Discord-style RP (aka "Markdown format") is not supported yet. The model does not include instruction tuning,
 only manually picked and slightly edited RP conversations with persona and scenario data.
 
+## Known issues
+- Due to software limitations, finetuning didn't take advantage yet of the Sliding Window Attention (SWA) which would have allowed
+to use longer conversations in the training data and a more accurate behavior with Scenario information. Thus, this version of LimaRP
+should be considered preliminary and will be updated in the future.
+- Despite performing a few finetuning attempts, including one that followed almost the same procedure as in previous releases,
+Mistral-7B-v0.1 appears to have strange repetition issues.
+- Even though benchmarks tell a different story, in practice the model doesn't feel smarter during roleplay than Llama-2-13B.
+
 ## Prompt format
 Same as before. It uses the [extended Alpaca format](https://github.com/tatsu-lab/stanford_alpaca),
 with `### Input:` immediately preceding user inputs and `### Response:` immediately preceding
@@ -131,4 +135,4 @@ the base Mistral-7B-v0.1 model.
 For the second pass, the `lora_model_dir` option was used to continue finetuning on the LoRA
 adapter obtained from the first pass.
 
-Using 2 GPUs, the effective global batch size would have been 8.
+Using 4 GPUs, the effective global batch size would have been 8.