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license: apache-2.0 |
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# Model Card for Deita Llama2 13B V1.0 SFT |
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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). |
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## Model description |
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- **Model type:** Model fine tuned on automatically selected lightweight, high-quality alignment SFT data. |
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- **Language(s) (NLP):** Primarily English |
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- **Finetuned from model:** [meta-llama/Llama-2-13b-hf](https://huggingface.co/meta-llama/Llama-2-13b-hf) |
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### Model Sources |
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- **Repository:** https://github.com/hkust-nlp/deita |
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- **Model Family:** Other models and the dataset are found in the [Deita collection](https://huggingface.co/collections/hkust-nlp/deita-6569c198c174808d94cf5bd4). |
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## Performance |
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## Input Format |
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The model is trained using the [vicuna_v1.1 template](https://github.com/lm-sys/FastChat/blob/main/fastchat/conversation.py) |
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``` |
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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: |
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``` |
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### Training hyperparameters |
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The following hyperparameters were used during fine tuning: |
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- learning_rate: 2e-05 |
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- total_train_batch_size: 128 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 3.0 |
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