---
base_model: deepseek-ai/deepseek-math-7b-base
library_name: peft
license: other
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: phi-3-mini-LoRA
  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. -->

# phi-3-mini-LoRA

This model is a fine-tuned version of [deepseek-ai/deepseek-math-7b-base](https://huggingface.co/deepseek-ai/deepseek-math-7b-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4014

## 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: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.4522        | 0.07  | 500  | 0.4533          |
| 0.4512        | 0.14  | 1000 | 0.4301          |
| 0.4386        | 0.21  | 1500 | 0.4199          |
| 0.4268        | 0.28  | 2000 | 0.4144          |
| 0.4167        | 0.35  | 2500 | 0.4104          |
| 0.3955        | 0.42  | 3000 | 0.4092          |
| 0.436         | 0.49  | 3500 | 0.4062          |
| 0.3912        | 0.55  | 4000 | 0.4057          |
| 0.425         | 0.62  | 4500 | 0.4036          |
| 0.4066        | 0.69  | 5000 | 0.4026          |
| 0.3963        | 0.76  | 5500 | 0.4016          |
| 0.3862        | 0.83  | 6000 | 0.4019          |
| 0.3902        | 0.9   | 6500 | 0.4015          |
| 0.4364        | 0.97  | 7000 | 0.4014          |


### Framework versions

- PEFT 0.8.2
- Transformers 4.38.0
- Pytorch 2.2.1
- Datasets 2.17.0
- Tokenizers 0.15.2