Instructions to use AdnanRiaz107/CodePhi-3.5-mini-0.4Klora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use AdnanRiaz107/CodePhi-3.5-mini-0.4Klora with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("microsoft/Phi-3.5-mini-instruct") model = PeftModel.from_pretrained(base_model, "AdnanRiaz107/CodePhi-3.5-mini-0.4Klora") - Notebooks
- Google Colab
- Kaggle
| license: mit | |
| library_name: peft | |
| tags: | |
| - generated_from_trainer | |
| base_model: microsoft/Phi-3.5-mini-instruct | |
| model-index: | |
| - name: CodePhi-3.5-mini-0.4Klora | |
| results: [] | |
| <!-- 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. --> | |
| # CodePhi-3.5-mini-0.4Klora | |
| This model is a fine-tuned version of [microsoft/Phi-3.5-mini-instruct](https://huggingface.co/microsoft/Phi-3.5-mini-instruct) on an unknown dataset. | |
| It achieves the following results on the evaluation set: | |
| - Loss: 0.6789 | |
| ## 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: 5e-06 | |
| - train_batch_size: 1 | |
| - eval_batch_size: 1 | |
| - seed: 42 | |
| - gradient_accumulation_steps: 16 | |
| - total_train_batch_size: 16 | |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 | |
| - lr_scheduler_type: cosine | |
| - lr_scheduler_warmup_steps: 40 | |
| - training_steps: 400 | |
| ### Training results | |
| | Training Loss | Epoch | Step | Validation Loss | | |
| |:-------------:|:-----:|:----:|:---------------:| | |
| | 0.603 | 0.25 | 100 | 0.7058 | | |
| | 0.6586 | 0.5 | 200 | 0.6842 | | |
| | 0.6558 | 0.75 | 300 | 0.6790 | | |
| | 0.6028 | 1.0 | 400 | 0.6789 | | |
| ### Framework versions | |
| - PEFT 0.11.0 | |
| - Transformers 4.40.2 | |
| - Pytorch 2.3.0+cu121 | |
| - Datasets 2.19.1 | |
| - Tokenizers 0.19.1 |