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README.md

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+# Model Card for Deita Llama2 13B V1.0 SFT
+
+Deita is an open-sourced project designed to facilitate Automatic Data Selection for instruction tuning in Large Language Models (LLMs). Deita Llama2 13B V1.0 SFT is a fine-tuned version of Llama 2 that was trained on 10k automatically selected lightweight, high-quality alignment SFT data: [Deita 10K V0](https://huggingface.co/datasets/hkust-nlp/deita-10k-v0).
+
+## Model description
+
+- **Model type:** Model fine tuned on automatically selected lightweight, high-quality alignment SFT data.
+- **Language(s) (NLP):** Primarily English
+- **Finetuned from model:** [meta-llama/Llama-2-13b-hf](https://huggingface.co/meta-llama/Llama-2-13b-hf)
+
+
+### Model Sources
+
+- **Repository:** https://github.com/hkust-nlp/deita
+- **Model Family:** Other models and the dataset are found in the [Deita collection](https://huggingface.co/collections/hkust-nlp/deita-6569c198c174808d94cf5bd4).
+
+## Performance
+
+
+## Input Format
+
+The model is trained using the [vicuna_v1.1 template](https://github.com/lm-sys/FastChat/blob/main/fastchat/conversation.py)
+
+```
+A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: Hello! ASSISTANT: Hi!</s>USER: How are you? ASSISTANT:
+```
+
+### Training hyperparameters
+
+The following hyperparameters were used during fine tuning:
+- learning_rate: 2e-05
+- total_train_batch_size: 128
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 3.0