| | --- |
| | license: mit |
| | library_name: peft |
| | tags: |
| | - generated_from_trainer |
| | base_model: microsoft/Phi-3-mini-128k-instruct |
| | model-index: |
| | - name: CodePhi-3-mini-128k-instruct-APPS |
| | results: [] |
| | datasets: |
| | - codeparrot/apps |
| | pipeline_tag: text-generation |
| | --- |
| | |
| | <!-- 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-mini-4k-instruct-APPS |
| |
|
| | This model is a fine-tuned version of [microsoft/Phi-3-mini-128k-instruct](https://huggingface.co/microsoft/Phi-3-mini-128k-instruct) on an unknown dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.7651 |
| |
|
| | ## 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: 100 |
| | - training_steps: 1200 |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | |
| | |:-------------:|:------:|:----:|:---------------:| |
| | | 0.8306 | 0.0833 | 100 | 0.8445 | |
| | | 0.6325 | 0.1667 | 200 | 0.8164 | |
| | | 0.6696 | 0.25 | 300 | 0.7934 | |
| | | 0.643 | 0.3333 | 400 | 0.7815 | |
| | | 0.778 | 0.4167 | 500 | 0.7737 | |
| | | 0.7273 | 0.5 | 600 | 0.7696 | |
| | | 0.712 | 0.5833 | 700 | 0.7676 | |
| | | 0.6477 | 0.6667 | 800 | 0.7658 | |
| | | 0.6245 | 0.75 | 900 | 0.7652 | |
| | | 0.6959 | 0.8333 | 1000 | 0.7650 | |
| | | 0.7236 | 0.9167 | 1100 | 0.7650 | |
| | | 0.6774 | 1.0 | 1200 | 0.7651 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - PEFT 0.11.0 |
| | - Transformers 4.40.2 |
| | - Pytorch 2.3.0+cu121 |
| | - Datasets 2.19.1 |
| | - Tokenizers 0.19.1 |
