| | --- |
| | 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 |
| | metrics: |
| | - accuracy |
| | - value: 40 |
| | --- |
| | |
| | # phi-2-basic-maths |
| |
|
| | This model is a fine-tuned version of [microsoft/phi-2](https://huggingface.co/microsoft/phi-2) on an [GSM8K dataset](https://huggingface.co/datasets/gsm8k). |
| |
|
| | ## Model Description |
| |
|
| | The objective of this model is to evaluate Phi-2's ability to provide correct solutions to reasoning problems after fine-tuning. This model was trained using techniques such as TRL, LoRA quantization, and Flash Attention. |
| |
|
| | To test it, you can use the following code: |
| |
|
| | ```python |
| | import torch |
| | from peft import AutoPeftModelForCausalLM |
| | from transformers import AutoTokenizer, pipeline |
| | |
| | # Specify the model ID |
| | peft_model_id = "Menouar/phi-2-basic-maths" |
| | |
| | # Load Model with PEFT adapter |
| | model = AutoPeftModelForCausalLM.from_pretrained( |
| | peft_model_id, |
| | device_map="auto", |
| | torch_dtype=torch.float16 |
| | ) |
| | |
| | tokenizer = AutoTokenizer.from_pretrained(peft_model_id) |
| | |
| | pipe = pipeline("text-generation", model=model, tokenizer=tokenizer) |
| | ``` |
| |
|
| | ## Training procedure |
| |
|
| | The complete training procedure can be found on my [Notebook](https://colab.research.google.com/drive/1mvfoEqc0mwuf8FqrABWt06qwAsU2QrvK). |
| |
|
| | ### 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: 30 |
| |
|
| | ### Training results |
| |
|
| | The training results can be found on [Tensoboard](https://huggingface.co/Menouar/phi-2-basic-maths/tensorboard). |
| |
|
| | ## Evaluation procedure |
| |
|
| | The complete Evaluation procedure can be found on my [Notebook](https://colab.research.google.com/drive/1xsdxOm-CgZmLAPFgp8iU9lLFEIIHGiUK). |
| |
|
| | ### Framework versions |
| |
|
| | - PEFT 0.8.2 |
| | - Transformers 4.38.0.dev0 |
| | - Pytorch 2.1.0+cu121 |
| | - Datasets 2.16.1 |
| | - Tokenizers 0.15.1 |
