---
library_name: peft
license: mit
base_model: microsoft/Phi-4-mini-instruct
tags:
- base_model:adapter:microsoft/Phi-4-mini-instruct
- lora
- transformers
model-index:
- name: phi4_instruct_20250902_0749
  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. -->

# phi4_instruct_20250902_0749

This model is a fine-tuned version of [microsoft/Phi-4-mini-instruct](https://huggingface.co/microsoft/Phi-4-mini-instruct) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6032
- Map@3: 0.8772

## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Map@3  |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 16.4003       | 0.0523 | 20   | 1.3662          | 0.7260 |
| 9.5268        | 0.1046 | 40   | 1.0851          | 0.7793 |
| 8.3438        | 0.1569 | 60   | 0.9705          | 0.7830 |
| 7.495         | 0.2092 | 80   | 0.9053          | 0.8070 |
| 7.4283        | 0.2615 | 100  | 0.8488          | 0.8326 |
| 6.5147        | 0.3138 | 120  | 0.7270          | 0.8505 |
| 5.6739        | 0.3661 | 140  | 0.7694          | 0.8445 |
| 5.8069        | 0.4184 | 160  | 0.6465          | 0.8692 |
| 5.8288        | 0.4707 | 180  | 0.6613          | 0.8537 |
| 4.7902        | 0.5230 | 200  | 0.6032          | 0.8827 |
| 5.0708        | 0.5754 | 220  | 0.5588          | 0.8832 |
| 4.7105        | 0.6277 | 240  | 0.5590          | 0.8880 |
| 4.6516        | 0.6800 | 260  | 0.5281          | 0.8944 |
| 4.2103        | 0.7323 | 280  | 0.5666          | 0.8824 |
| 4.9022        | 0.7846 | 300  | 0.5486          | 0.8936 |
| 3.8328        | 0.8369 | 320  | 0.5402          | 0.8959 |
| 4.2973        | 0.8892 | 340  | 0.5149          | 0.9046 |
| 3.8971        | 0.9415 | 360  | 0.4942          | 0.8943 |
| 3.9711        | 0.9938 | 380  | 0.5736          | 0.8894 |
| 3.6985        | 1.0445 | 400  | 0.5119          | 0.9000 |
| 2.971         | 1.0968 | 420  | 0.6032          | 0.8772 |


### Framework versions

- PEFT 0.17.1
- Transformers 4.56.0
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.0