---
license: mit
library_name: peft
tags:
- trl
- sft
- generated_from_trainer
datasets:
- generator
base_model: microsoft/phi-2
model-index:
- name: phi2_fine_tune_istanbul_rugs
  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. -->

# phi2_fine_tune_istanbul_rugs

This model is a fine-tuned version of [microsoft/phi-2](https://huggingface.co/microsoft/phi-2) on the generator dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8105

## 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: 0.0008
- train_batch_size: 2
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- training_steps: 300

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.6408        | 0.72  | 10   | 0.5720          |
| 0.4116        | 1.45  | 20   | 0.5234          |
| 0.3467        | 2.17  | 30   | 0.5068          |
| 0.328         | 2.9   | 40   | 0.4990          |
| 0.3013        | 3.62  | 50   | 0.5022          |
| 0.267         | 4.34  | 60   | 0.5051          |
| 0.2407        | 5.07  | 70   | 0.5151          |
| 0.2084        | 5.79  | 80   | 0.5329          |
| 0.1821        | 6.52  | 90   | 0.5566          |
| 0.1635        | 7.24  | 100  | 0.5996          |
| 0.1431        | 7.96  | 110  | 0.6137          |
| 0.1164        | 8.69  | 120  | 0.6461          |
| 0.1045        | 9.41  | 130  | 0.6714          |
| 0.0903        | 10.14 | 140  | 0.6719          |
| 0.0773        | 10.86 | 150  | 0.6802          |
| 0.0653        | 11.58 | 160  | 0.7234          |
| 0.0595        | 12.31 | 170  | 0.7497          |
| 0.0523        | 13.03 | 180  | 0.7281          |
| 0.0453        | 13.76 | 190  | 0.7439          |
| 0.0405        | 14.48 | 200  | 0.7655          |
| 0.0363        | 15.2  | 210  | 0.7674          |
| 0.0323        | 15.93 | 220  | 0.7835          |
| 0.0293        | 16.65 | 230  | 0.7924          |
| 0.0276        | 17.38 | 240  | 0.7981          |
| 0.0257        | 18.1  | 250  | 0.8023          |
| 0.0252        | 18.82 | 260  | 0.8019          |
| 0.0236        | 19.55 | 270  | 0.8040          |
| 0.023         | 20.27 | 280  | 0.8089          |
| 0.0232        | 21.0  | 290  | 0.8104          |
| 0.0231        | 21.72 | 300  | 0.8105          |


### Framework versions

- PEFT 0.9.0
- Transformers 4.38.1
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2