|
|
--- |
|
|
license: mit |
|
|
library_name: peft |
|
|
tags: |
|
|
- generated_from_trainer |
|
|
base_model: microsoft/Phi-3-mini-4k-instruct |
|
|
model-index: |
|
|
- name: CodePhi-3-mini-4k-instruct-pythonAPPSLORA3k |
|
|
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-mini-4k-instruct-pythonAPPSLORA3k |
|
|
|
|
|
This model is a fine-tuned version of [microsoft/Phi-3-mini-4k-instruct](https://huggingface.co/microsoft/Phi-3-mini-4k-instruct) on an unknown dataset. |
|
|
It achieves the following results on the evaluation set: |
|
|
- Loss: 0.6463 |
|
|
|
|
|
## 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: 200 |
|
|
- training_steps: 3000 |
|
|
|
|
|
### Training results |
|
|
|
|
|
| Training Loss | Epoch | Step | Validation Loss | |
|
|
|:-------------:|:------:|:----:|:---------------:| |
|
|
| 0.664 | 0.0667 | 200 | 0.7185 | |
|
|
| 0.642 | 0.1333 | 400 | 0.6786 | |
|
|
| 0.6163 | 0.2 | 600 | 0.6618 | |
|
|
| 0.5852 | 0.2667 | 800 | 0.6543 | |
|
|
| 0.5608 | 0.3333 | 1000 | 0.6519 | |
|
|
| 0.6224 | 0.4 | 1200 | 0.6499 | |
|
|
| 0.5984 | 0.4667 | 1400 | 0.6484 | |
|
|
| 0.5635 | 0.5333 | 1600 | 0.6474 | |
|
|
| 0.5687 | 0.6 | 1800 | 0.6468 | |
|
|
| 0.6199 | 0.6667 | 2000 | 0.6465 | |
|
|
| 0.5785 | 0.7333 | 2200 | 0.6463 | |
|
|
| 0.594 | 0.8 | 2400 | 0.6463 | |
|
|
| 0.5622 | 0.8667 | 2600 | 0.6463 | |
|
|
| 0.5791 | 0.9333 | 2800 | 0.6462 | |
|
|
| 0.5964 | 1.0 | 3000 | 0.6463 | |
|
|
|
|
|
|
|
|
### Framework versions |
|
|
|
|
|
- PEFT 0.11.0 |
|
|
- Transformers 4.40.2 |
|
|
- Pytorch 2.3.0+cu121 |
|
|
- Datasets 2.19.1 |
|
|
- Tokenizers 0.19.1 |
