---
base_model: microsoft/Phi-3.5-mini-instruct
library_name: peft
license: mit
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: Phi-3.5-mini-instruct-qlora
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Phi-3.5-mini-instruct-qlora

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: 0.8242

## 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: 0.0001
- train_batch_size: 4
- eval_batch_size: 4
- seed: 0
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.01
- num_epochs: 4

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.6254        | 0.3333 | 10   | 1.2928          |
| 1.0852        | 0.6667 | 20   | 0.9771          |
| 0.8786        | 1.0    | 30   | 0.8939          |
| 0.7889        | 1.3333 | 40   | 0.8575          |
| 0.7281        | 1.6667 | 50   | 0.8336          |
| 0.6876        | 2.0    | 60   | 0.8175          |
| 0.6217        | 2.3333 | 70   | 0.8238          |
| 0.6066        | 2.6667 | 80   | 0.8274          |
| 0.614         | 3.0    | 90   | 0.8193          |
| 0.5568        | 3.3333 | 100  | 0.8235          |
| 0.5435        | 3.6667 | 110  | 0.8242          |
| 0.5699        | 4.0    | 120  | 0.8242          |


### Framework versions

- PEFT 0.13.2
- Transformers 4.46.0
- Pytorch 2.4.0
- Datasets 3.0.2
- Tokenizers 0.20.0