---
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-appsloraN1k5.0e-6ada
  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-128k-instruct-appsloraN1k5.0e-6ada

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: 0.6586

## 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: 1000

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.5978        | 0.1   | 100  | 0.7032          |
| 0.6563        | 0.2   | 200  | 0.6818          |
| 0.6499        | 0.3   | 300  | 0.6716          |
| 0.5934        | 0.4   | 400  | 0.6659          |
| 0.6196        | 0.5   | 500  | 0.6621          |
| 0.605         | 0.6   | 600  | 0.6599          |
| 0.6086        | 0.7   | 700  | 0.6589          |
| 0.5696        | 0.8   | 800  | 0.6587          |
| 0.5855        | 0.9   | 900  | 0.6587          |
| 0.5424        | 1.0   | 1000 | 0.6586          |


### Framework versions

- PEFT 0.11.0
- Transformers 4.40.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1