---
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