Update README.md (#3)

- Update README.md (c4ec16a65abe020b1e85dd5e2f0618984fe5b36f)


Co-authored-by: Ariel Lee <[email protected]>

README.md

@@ -13,7 +13,7 @@ metrics:
 
 # 🥳 Platypus-30B has arrived! 
 
-Platypus-30B is an instruction fine-tuned model based on the LLaMA-30b transformer architecture.
+Platypus-30B is an instruction fine-tuned model based on the LLaMA-30B transformer architecture and takes advantage of [LoRA]([LoRA](https://arxiv.org/pdf/2106.09685.pdf).
 
 | Metric                | Value |
 |-----------------------|-------|
@@ -21,18 +21,11 @@ Platypus-30B is an instruction fine-tuned model based on the LLaMA-30b transform
 | ARC (25-shot)         | 64.6  |
 | HellaSwag (10-shot)   | 84.3  |
 | TruthfulQA (0-shot)   | 45.8  |
-|-----------------------|-------|
-| Avg.                  | 65    | 💥
-
-## Usage
-
-```sh
-ADD
-```
+| Avg.                  | 65    | 
 
 ## Model Details
 
-* **Trained by**: [Ariel Lee & Cole Hunter, LINK TO WEBSITES]
+* **Trained by**: Cole Hunter & Ariel Lee
 * **Model type:**  **Platypus-30B** is an auto-regressive language model based on the LLaMA transformer architecture.
 * **Language(s)**: English
 * **License for base weights**: License for the base LLaMA model's weights is Meta's [non-commercial bespoke license](https://github.com/facebookresearch/llama/blob/main/MODEL_CARD.md).
@@ -50,21 +43,7 @@ Dataset of highly filtered and curated question and answer pairs. Release TBD.
 
 ## Training Procedure
 
-`lilloukas/Platypus-30b` was instruction fine-tuned using lora [CITE REPO] on 4 A100 80GB with the following configuration:
-
-| Hyperparameter      | Value |
-|---------------------|-------|
-| learning_rate       | ---   |
-| batch_size          | ---   |
-| microbatch_size     | ---   |
-| warmup_steps        | ---   |
-| epochs              | ---   |
-| weight_decay        | ---   |
-| optimizer           | ---   |
-| weight_decay        | ---   |
-| cutoff_len          | ---   |
-| lora_target_modules | ---   |
-
+`lilloukas/Platypus-30B` was instruction fine-tuned using LoRA on 4 A100 80GB. For training details and inference instructions please see the [Platypus-30B](https://github.com/arielnlee/Platypus-30B.git) GitHub repo.
 
 ## Limitations and bias