Update README.md

README.md

@@ -1,10 +1,5 @@
 ---
-datasets:
-  - sciq
-  - metaeval/ScienceQA_text_only
-  - GAIR/lima
-  - Open-Orca/OpenOrca
-  - openbookqa
+ 
 language:
 - en
 tags:
@@ -16,12 +11,82 @@ pipeline_tag: text-generation
 ---
 # LLaMa-65b-instruct model card
 
-## Contact Us, Why Upstage LLM?
-- [Upstage](https://en.upstage.ai)'s LLM research has yielded remarkable results. Our 30B model **outperforms all models around the world**,  positioning itself as the leading performer. Recognizing the immense potential in implementing private LLM to actual businesses, we invite you to easily apply private LLM and fine-tune it with your own data. For a seamless and tailored solution, please do not hesitate to reach out to us. ► [click here to contact].
+## Model Details
 
-## Model and Dataset Details
-- Please refer to the model card of [upstage/llama-30b-instruct](https://huggingface.co/upstage/llama-30b-instruct) as this one is almost the same.
+* **Developed by**: [Upstage](https://en.upstage.ai)
+* **Backbone Model**: [LLaMA](https://github.com/facebookresearch/llama/tree/llama_v1)
+* **Variations**: It has different model parameter sizes and sequence lengths: [30B/1024](https://huggingface.co/upstage/llama-30b-instruct), [30B/2048](https://huggingface.co/upstage/llama-30b-instruct-2048), [65B/1024](https://huggingface.co/upstage/llama-65b-instruct)
+* **Language(s)**: English
+* **Library**: [HuggingFace Transformers](https://github.com/huggingface/transformers)
+* **License**: This model is under a **Non-commercial** Bespoke License and governed by the Meta license. You should only use this repository if you have been granted access to the model by filling out [this form](https://docs.google.com/forms/d/e/1FAIpQLSfqNECQnMkycAp2jP4Z9TFX0cGR4uf7b_fBxjY_OjhJILlKGA/viewform), but have either lost your copy of the weights or encountered issues converting them to the Transformers format
+* **Where to send comments**: Instructions on how to provide feedback or comments on a model can be found by opening an issue in the [Hugging Face community's model repository](https://huggingface.co/upstage/llama-30b-instruct-2048/discussions)
+* **Contact**: For questions and comments about the model, please email [[email protected]](mailto:[email protected])
 
+## Dataset Details
+
+### Used Datasets
+
+- Internal Orca-style dataset
+
+> No other data was used except for the dataset mentioned above
+
+### Prompt Template
+```
+### System:
+{System}
+
+### User:
+{User}
+
+### Assistant:
+{Assistant}
+```
+
+## Hardware and Software
+
+* **Hardware**: We utilized an A100x8 * 4 for training our model
+* **Training Factors**: We fine-tuned this model using a combination of the [DeepSpeed library](https://github.com/microsoft/DeepSpeed) and the [HuggingFace trainer](https://huggingface.co/docs/transformers/main_classes/trainer)
+
+## Evaluation Results
+
+### Overview
+- We conducted a performance evaluation based on the tasks being evaluated on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).
+We evaluated our model on four benchmark datasets, which include `ARC-Challenge`, `HellaSwag`, `MMLU`, and `TruthfulQA`.
+We used the [lm-evaluation-harness repository](https://github.com/EleutherAI/lm-evaluation-harness), specifically commit [b281b0921b636bc36ad05c0b0b0763bd6dd43463](https://github.com/EleutherAI/lm-evaluation-harness/tree/b281b0921b636bc36ad05c0b0b0763bd6dd43463).
+
+### Main Results
+| Model                                         | Average | ARC   | HellaSwag | MMLU  | TruthfulQA |
+|-----------------------------------------------|---------|-------|-----------|-------|------------|
+| Llama-2-70b-instruct-v2 (Ours, Local Reproduction) | 72.7 | 71.6 | 87.7 | 69.7 | 61.6 |
+| Llama-2-70b-instruct (Ours, Local Reproduction) | 72.0 | 70.7 | 87.4 | 69.3 | 60.7 |
+| **llama-65b-instruct (Ours, Local Reproduction)** | **69.4** | **67.6** | **86.5** | **64.9** | **58.8** |
+| Llama-2-70b-hf | 67.3 | 67.3 | 87.3 | 69.8 | 44.9 |
+| llama-30b-instruct-2048 (Ours, Open LLM Leaderboard) | 67.0 | 64.9 | 84.9 | 61.9 | 56.3 |
+| llama-30b-instruct-2048 (Ours, Local Reproduction) | 67.0 | 64.9 | 85.0 | 61.9 | 56.0 |
+| llama-30b-instruct (Ours, Open LLM Leaderboard) | 65.2 | 62.5 | 86.2 | 59.4 | 52.8 |
+| llama-65b | 64.2 | 63.5 | 86.1 | 63.9 | 43.4 |
+| falcon-40b-instruct | 63.4 | 61.6 | 84.3 | 55.4 | 52.5 |
+
+
+### Scripts
+- Prepare evaluation environments:
+```
+# clone the repository
+git clone https://github.com/EleutherAI/lm-evaluation-harness.git
+
+# check out the specific commit
+git checkout b281b0921b636bc36ad05c0b0b0763bd6dd43463
+
+# change to the repository directory
+cd lm-evaluation-harness
+```
+
+## Ethical Issues
+
+### Ethical Considerations
+- There were no ethical issues involved, as we did not include the benchmark test set or the training set in the model's training process.
+
+## Contact Us
 
 ### Why Upstage LLM?
 - [Upstage](https://en.upstage.ai)'s LLM research has yielded remarkable results. Our 30B model **outperforms all models around the world**,  positioning itself as the leading performer. Recognizing the immense potential in implementing private LLM to actual businesses, we invite you to easily apply private LLM and fine-tune it with your own data. For a seamless and tailored solution, please do not hesitate to reach out to us. ► [click here to contact](https://www.upstage.ai/private-llm?utm_source=huggingface&utm_medium=link&utm_campaign=privatellm).