---
license: mit
library_name: peft
tags:
- generated_from_trainer
base_model: AdnanRiaz107/CodePhi-3-mini-4k-instruct-python
model-index:
- name: CodePhi-3-mini-4k-instruct-pythonAPPS
  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-pythonAPPS

This model is a fine-tuned version of [AdnanRiaz107/CodePhi-3-mini-4k-instruct-python](https://huggingface.co/AdnanRiaz107/CodePhi-3-mini-4k-instruct-python) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6522

## 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 |
|:-------------:|:------:|:----:|:---------------:|
| 0.5844        | 0.0833 | 100  | 0.6866          |
| 0.6441        | 0.1667 | 200  | 0.6737          |
| 0.6551        | 0.25   | 300  | 0.6658          |
| 0.5858        | 0.3333 | 400  | 0.6605          |
| 0.6136        | 0.4167 | 500  | 0.6569          |
| 0.5982        | 0.5    | 600  | 0.6546          |
| 0.6           | 0.5833 | 700  | 0.6531          |
| 0.5609        | 0.6667 | 800  | 0.6525          |
| 0.5824        | 0.75   | 900  | 0.6523          |
| 0.538         | 0.8333 | 1000 | 0.6523          |
| 0.6339        | 0.9167 | 1100 | 0.6523          |
| 0.6138        | 1.0    | 1200 | 0.6522          |


### Framework versions

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