Text Generation
PEFT
TensorBoard
Safetensors
PyTorch
English
trl
sft
Generated from Trainer
Eval Results (legacy)
Instructions to use Menouar/phi-2-basic-maths with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Menouar/phi-2-basic-maths with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("microsoft/phi-2") model = PeftModel.from_pretrained(base_model, "Menouar/phi-2-basic-maths") - Notebooks
- Google Colab
- Kaggle
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Download README.md from Menouar/phi-2-basic-maths: direct link, hf CLI and curl.
- Browser
- Download file 1.21 kB
-
https://huggingface.co/Menouar/phi-2-basic-maths/resolve/dcdc93464a7ceb6767e48639ef73751ae9c8b355/README.md
- Command line
-
hf download hf://Menouar/phi-2-basic-maths@dcdc93464a7ceb6767e48639ef73751ae9c8b355/README.md
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curl -L -o README.md https://huggingface.co/Menouar/phi-2-basic-maths/resolve/dcdc93464a7ceb6767e48639ef73751ae9c8b355/README.md
1.21 kB
| license: mit | |
| library_name: peft | |
| tags: | |
| - trl | |
| - sft | |
| - generated_from_trainer | |
| base_model: microsoft/phi-2 | |
| model-index: | |
| - name: phi-2-basic-maths | |
| results: [] | |
| datasets: | |
| - gsm8k | |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You | |
| should probably proofread and complete it, then remove this comment. --> | |
| # phi-2-basic-maths | |
| This model is a fine-tuned version of [microsoft/phi-2](https://huggingface.co/microsoft/phi-2) on GSMK8 dataset. | |
| ## Model description | |
| More information needed | |
| ## Intended uses & limitations | |
| More information needed | |
| ## Training and evaluation data | |
| More information needed | |
| ## Training procedure | |
| ### Training hyperparameters | |
| The following hyperparameters were used during training: | |
| - learning_rate: 0.0002 | |
| - train_batch_size: 42 | |
| - eval_batch_size: 8 | |
| - seed: 42 | |
| - gradient_accumulation_steps: 2 | |
| - total_train_batch_size: 84 | |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 | |
| - lr_scheduler_type: constant | |
| - lr_scheduler_warmup_ratio: 0.03 | |
| - num_epochs: 10 | |
| ### Training results | |
| ### Framework versions | |
| - PEFT 0.8.2 | |
| - Transformers 4.38.0.dev0 | |
| - Pytorch 2.1.0+cu121 | |
| - Datasets 2.16.1 | |
| - Tokenizers 0.15.1 |