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--- |
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license: apache-2.0 |
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tags: |
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- alignment-handbook |
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- generated_from_trainer |
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- trl |
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- sft |
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- generated_from_trainer |
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datasets: |
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- jan-hq/bagel_sft_binarized |
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- jan-hq/dolphin_binarized |
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- jan-hq/openhermes_binarized |
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- jan-hq/bagel_dpo_binarized |
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base_model: TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T |
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pipeline_tag: text-generation |
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inference: |
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parameters: |
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temperature: 0.7 |
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max_new_tokens: 40 |
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widget: |
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- messages: |
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- role: user |
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content: Tell me about NVIDIA in 20 words |
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--- |
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<!-- header start --> |
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<!-- 200823 --> |
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<div style="width: auto; margin-left: auto; margin-right: auto" |
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> |
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<img src="https://github.com/janhq/jan/assets/89722390/35daac7d-b895-487c-a6ac-6663daaad78e" alt="Jan banner" |
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style="width: 100%; min-width: 400px; display: block; margin: auto;"> |
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</div> |
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<p align="center"> |
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<a href="https://jan.ai/">Jan</a |
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> |
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- <a |
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href="https://discord.gg/AsJ8krTT3N">Discord</a> |
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</p> |
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<!-- header end --> |
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# Model description |
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- Finetuned [TinyLlama-1.1B](TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T) further for handling simple tasks and have acceptable conversational quality |
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- Utilized high-quality opensource dataset |
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- Can be run on [TensorRT-LLM](https://github.com/NVIDIA/TensorRT-LLM) on consumer devices |
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- Can fit into laptop dGPUs with as little as >=6gb of VRAM |
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# Prompt template |
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ChatML |
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``` |
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<|im_start|>system |
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{system_message}<|im_end|> |
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<|im_start|>user |
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{prompt}<|im_end|> |
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<|im_start|>assistant |
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``` |
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# Run this model |
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You can run this model using [Jan Desktop](https://jan.ai/) on Mac, Windows, or Linux. |
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Jan is an open source, ChatGPT alternative that is: |
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- 💻 **100% offline on your machine**: Your conversations remain confidential, and visible only to you. |
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- 🗂️ ** |
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An Open File Format**: Conversations and model settings stay on your computer and can be exported or deleted at any time. |
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- 🌐 **OpenAI Compatible**: Local server on port `1337` with OpenAI compatible endpoints |
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- 🌍 **Open Source & Free**: We build in public; check out our [Github](https://github.com/janhq) |
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 |
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# About Jan |
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Jan believes in the need for an open-source AI ecosystem and is building the infra and tooling to allow open-source AIs to compete on a level playing field with proprietary ones. |
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Jan's long-term vision is to build a cognitive framework for future robots, who are practical, useful assistants for humans and businesses in everyday life. |
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# LlamaCorn-1.1B-Chat |
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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: 5e-07 |
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- train_batch_size: 2 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 2 |
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- gradient_accumulation_steps: 16 |
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- total_train_batch_size: 64 |
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- total_eval_batch_size: 8 |
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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_ratio: 0.1 |
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- num_epochs: 3 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen | |
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|:-------------:|:-----:|:-----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:| |
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| 0.9958 | 0.03 | 100 | 1.0003 | -0.0002 | -0.0002 | 0.4930 | -0.0001 | -180.9232 | -195.6078 | -2.6876 | -2.6924 | |
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| 0.9299 | 1.02 | 3500 | 0.9439 | -0.1570 | -0.2195 | 0.5770 | 0.0625 | -183.1160 | -197.1755 | -2.6612 | -2.6663 | |
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| 0.9328 | 2.01 | 6900 | 0.9313 | -0.2127 | -0.2924 | 0.5884 | 0.0798 | -183.8456 | -197.7321 | -2.6296 | -2.6352 | |
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| 0.9321 | 2.98 | 10200 | 0.9305 | -0.2149 | -0.2955 | 0.5824 | 0.0805 | -183.8759 | -197.7545 | -2.6439 | -2.6493 | |
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### Framework versions |
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- Transformers 4.36.2 |
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- Pytorch 2.1.2+cu121 |
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- Datasets 2.14.6 |
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- Tokenizers 0.15.0 |
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# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard) |
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Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_jan-hq__LlamaCorn-1.1B) |
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| Metric |Value| |
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|---------------------------------|----:| |
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|Avg. |36.94| |
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|AI2 Reasoning Challenge (25-Shot)|34.13| |
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|HellaSwag (10-Shot) |59.33| |
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|MMLU (5-Shot) |29.01| |
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|TruthfulQA (0-shot) |36.78| |
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|Winogrande (5-shot) |61.96| |
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|GSM8k (5-shot) | 0.45| |
