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--- |
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license: apache-2.0 |
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base_model: openchat/openchat_3.5 |
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datasets: |
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- HuggingFaceH4/no_robots |
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language: |
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- en |
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tags: |
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- generated_from_trainer |
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pipeline_tag: text-generation |
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model-index: |
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- name: smol-7b |
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results: [] |
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--- |
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# Smol 7B |
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This model is a fine-tuned version of [openchat/openchat_3.5](https://huggingface.co/openchat/openchat_3.5) on the open source dataset [HuggingFaceH4/no_robots](https://huggingface.co/datasets/HuggingFaceH4/no_robots) using the recipes published in [The Alignment Handbook](https://github.com/huggingface/alignment-handbook). |
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## Model date |
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rishiraj/smol-7b was trained between 1st and 3rd December, 2023. |
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## Evaluation |
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It achieves the following results on the [Open_LLM_Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). At the time of release, smol-7b is the highest ranked 7B chat model on the [MMLU Benchmark](https://paperswithcode.com/sota/multi-task-language-understanding-on-mmlu). |
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| Model | Average | ARC | HellaSwag | MMLU | TruthfulQA | Winogrande | GSM8K | |
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| ---------------------------- | ------- | ----- | --------- | ----- | ---------- | ---------- | ----- | |
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| **rishiraj/smol-7b | 67.11 | 63.74 | 84.77 | 65 | 46.17 | 80.66 | 62.32** | |
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| argilla/notus-7b-v1 | 63.49 | 64.59 | 84.83 | 63.04 | 54.35 | 79.56 | 34.57 | |
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| Intel/neural-chat-7b-v3-1 | 61.59 | 66.21 | 83.64 | 62.37 | 59.65 | 78.14 | 19.56 | |
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| HuggingFaceH4/zephyr-7b-beta | 61.59 | 62.46 | 84.35 | 60.7 | 57.83 | 77.11 | 27.07 | |
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| Qwen/Qwen-7B | 59.19 | 51.37 | 78.47 | 59.84 | 47.79 | 72.69 | 44.96 | |
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| microsoft/Orca-2-7b | 54.55 | 54.1 | 76.19 | 56.37 | 52.45 | 73.48 | 14.71 | |
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| 01-ai/Yi-6B | 54.08 | 55.55 | 76.57 | 64.11 | 41.96 | 74.19 | 12.13 | |
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## Inference procedure |
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Here's how you can run the model using the pipeline() function from 🤗 Transformers: |
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``` |
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import torch |
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from transformers import pipeline |
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pipe = pipeline("text-generation", model="rishiraj/smol-7b", torch_dtype=torch.bfloat16, device_map="auto") |
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# We use the tokenizer's chat template to format each message - see https://huggingface.co/docs/transformers/main/en/chat_templating |
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messages = [ |
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{ |
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"role": "system", |
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"content": "You are a friendly chatbot who always responds in the style of a pirate" |
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}, |
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{ |
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"role": "user", |
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"content": "How many helicopters can a human eat in one sitting?" |
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} |
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] |
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prompt = pipe.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True) |
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outputs = pipe(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95) |
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print(outputs[0]["generated_text"]) |
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``` |
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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: 4 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- gradient_accumulation_steps: 128 |
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- total_train_batch_size: 512 |
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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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- num_epochs: 1 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 2.0569 | 0.16 | 3 | 2.0409 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.1+cu121 |
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- Datasets 2.14.6 |
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- Tokenizers 0.14.1 |
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## Citation Information |
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``` |
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@misc{rishiraj2023smol, |
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author = {Rishiraj Acharya}, |
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title = {Smol 7B}, |
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year = {2023}, |
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publisher = {Hugging Face}, |
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journal = {Hugging Face repository}, |
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howpublished = {\url{https://huggingface.co/rishiraj/smol-7b}} |
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} |
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``` |
