| library_name: peft | |
| tags: | |
| - meta-llama/Llama-2-7b-hf | |
| - code | |
| - instruct | |
| - instruct-code | |
| - logical-reasoning | |
| - Platypus2 | |
| datasets: | |
| - garage-bAInd/Open-Platypus | |
| base_model: meta-llama/Llama-2-7b-hf | |
| We finetuned Meta-Llama/Llama-2-7b-hf on the Open-Platypus dataset (garage-bAInd/Open-Platypus) for 5 epochs using [MonsterAPI](https://monsterapi.ai) no-code [LLM finetuner](https://docs.monsterapi.ai/fine-tune-a-large-language-model-llm). | |
| #### About OpenPlatypus Dataset | |
| OpenPlatypus is focused on improving LLM logical reasoning skills and was used to train the Platypus2 models. The dataset is comprised of various sub-datasets, including PRM800K, ScienceQA, SciBench, ReClor, TheoremQA, among others. These were filtered using keyword search and Sentence Transformers to remove questions with a similarity above 80%. The dataset includes contributions under various licenses like MIT, Creative Commons, and Apache 2.0. | |
| The finetuning session got completed in 1 hour and 30 minutes and costed us only `$15` for the entire finetuning run! | |
| #### Hyperparameters & Run details: | |
| - Model Path: meta-llama/Llama-2-7b-hf | |
| - Dataset: garage-bAInd/Open-Platypus | |
| - Learning rate: 0.0002 | |
| - Number of epochs: 5 | |
| - Data split: Training: 90% / Validation: 10% | |
| - Gradient accumulation steps: 1 | |
| --- | |
| license: apache-2.0 | |
| --- | |