---
license: mit
library_name: peft
tags:
- generated_from_trainer
base_model: microsoft/Phi-3.5-mini-instruct
model-index:
- name: phi3.5-hugcoder
  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. -->

# phi3.5-hugcoder

This model is a fine-tuned version of [microsoft/Phi-3.5-mini-instruct](https://huggingface.co/microsoft/Phi-3.5-mini-instruct) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6832

## 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: 0.0003
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 100

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| No log        | 0.1   | 10   | 0.5937          |
| No log        | 0.2   | 20   | 0.4756          |
| No log        | 0.3   | 30   | 0.4394          |
| No log        | 0.4   | 40   | 0.4419          |
| 0.5311        | 0.5   | 50   | 0.4827          |
| 0.5311        | 0.6   | 60   | 0.5897          |
| 0.5311        | 0.7   | 70   | 0.5495          |
| 0.5311        | 0.8   | 80   | 0.6268          |
| 0.5311        | 0.9   | 90   | 0.6744          |
| 0.1769        | 1.0   | 100  | 0.6832          |


### Framework versions

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