---
library_name: peft
license: mit
base_model: microsoft/Phi-4-mini-instruct
tags:
- llama-factory
- lora
- generated_from_trainer
model-index:
- name: Phi-4-mini-instruct_sft_sg_values_resp_split
  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-4-mini-instruct_sft_sg_values_resp_split

This model is a fine-tuned version of [microsoft/Phi-4-mini-instruct](https://huggingface.co/microsoft/Phi-4-mini-instruct) on the sft_sg_values_res_split dataset.
It achieves the following results on the evaluation set:
- Loss: 2.3214

## 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: 1e-06
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1.0

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 4.3698        | 0.1710 | 250  | 4.1731          |
| 3.5096        | 0.3419 | 500  | 3.1497          |
| 2.6213        | 0.5129 | 750  | 2.5736          |
| 2.4305        | 0.6839 | 1000 | 2.3980          |
| 2.3653        | 0.8548 | 1250 | 2.3345          |


### Framework versions

- PEFT 0.15.2
- Transformers 4.51.1
- Pytorch 2.6.0+cu124
- Datasets 3.2.0
- Tokenizers 0.21.1