---
base_model: microsoft/Phi-3.5-mini-instruct
library_name: peft
license: mit
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 [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: 0.3840

## 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: 0.0002
- train_batch_size: 4
- eval_batch_size: 4
- seed: 3407
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 5
- training_steps: 120

### Training results

| Training Loss | Epoch   | Step | Validation Loss |
|:-------------:|:-------:|:----:|:---------------:|
| 1.5071        | 0.5882  | 5    | 1.4674          |
| 1.1659        | 1.1765  | 10   | 1.0849          |
| 0.894         | 1.7647  | 15   | 0.8655          |
| 0.7243        | 2.3529  | 20   | 0.6989          |
| 0.5752        | 2.9412  | 25   | 0.5856          |
| 0.5724        | 3.5294  | 30   | 0.5257          |
| 0.4834        | 4.1176  | 35   | 0.4875          |
| 0.3861        | 4.7059  | 40   | 0.4588          |
| 0.35          | 5.2941  | 45   | 0.4368          |
| 0.3126        | 5.8824  | 50   | 0.4251          |
| 0.367         | 6.4706  | 55   | 0.4080          |
| 0.2792        | 7.0588  | 60   | 0.3955          |
| 0.3952        | 7.6471  | 65   | 0.3914          |
| 0.2854        | 8.2353  | 70   | 0.3784          |
| 0.3224        | 8.8235  | 75   | 0.3867          |
| 0.3187        | 9.4118  | 80   | 0.3765          |
| 0.1675        | 10.0    | 85   | 0.3799          |
| 0.1888        | 10.5882 | 90   | 0.3858          |
| 0.2021        | 11.1765 | 95   | 0.3759          |
| 0.1518        | 11.7647 | 100  | 0.3868          |
| 0.2075        | 12.3529 | 105  | 0.3915          |
| 0.1497        | 12.9412 | 110  | 0.3814          |
| 0.1797        | 13.5294 | 115  | 0.3821          |
| 0.1606        | 14.1176 | 120  | 0.3840          |


### Framework versions

- PEFT 0.13.2
- Transformers 4.45.2
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.20.0