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--- |
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base_model: NousResearch/Llama-2-13b-hf |
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tags: |
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- llama-2 |
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- instruct |
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- finetune |
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- alpaca |
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- gpt4 |
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- synthetic data |
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model-index: |
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- name: openhermes-13b |
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results: [] |
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license: mit |
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language: |
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- en |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# OpenHermes-13B |
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## Model description |
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OpenHermes 13B is the first fine tune of the Hermes dataset that has a fully open source dataset! |
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OpenHermes was trained on 242,000 entries of primarily GPT-4 generated data, from open datasets across the AI landscape, including: |
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- GPTeacher - General Instruct, Roleplay v1, Roleplay v2, and Code Instruct Datasets, by Teknium |
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- WizardLM (v1, evol_instruct 70k), by WizardLM Team/nlpxucan |
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- Airoboros GPT-4 (v1.0), by JonDurbin |
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- Camel-AI's domain expert datasets, by the Camel-AI Team |
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- CodeAlpaca, by Sahil2801 |
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- GPT4-LLM and Unnatural Instructions, by Microsoft |
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Filtering included removal of OpenAI refusals, disclaimers, and "As an AI" type examples and more |
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The base dataset mix the model was trained on is identical to Nous-Hermes', minus the Nous-Instruct and PDACTL datasets which were private datasets. |
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## Benchmark Information |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2e-05 |
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- train_batch_size: 2 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 8 |
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- gradient_accumulation_steps: 8 |
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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: cosine |
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- lr_scheduler_warmup_steps: 300 |
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- num_epochs: 3 |
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### Framework versions |
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- Transformers 4.34.0.dev0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.4 |
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- Tokenizers 0.13.3 |