---
license: mit
library_name: peft
tags:
- generated_from_trainer
base_model: microsoft/Phi-3-mini-128k-instruct
model-index:
- name: CodePhi-3-mini-0.06Klora
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# CodePhi-3-mini-0.06Klora

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: 0.7056

## 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: 6
- training_steps: 60

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.7307        | 0.1667 | 10   | 0.7108          |
| 0.6895        | 0.3333 | 20   | 0.7088          |
| 0.6816        | 0.5    | 30   | 0.7071          |
| 0.6974        | 0.6667 | 40   | 0.7060          |
| 0.5756        | 0.8333 | 50   | 0.7056          |
| 0.3683        | 1.0    | 60   | 0.7056          |


### Framework versions

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