---
base_model: microsoft/Phi-3.5-mini-instruct
library_name: peft
license: mit
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: question-generator-v2
  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. -->

# question-generator-v2

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: 0.7497

## 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: 0.0005
- train_batch_size: 8
- eval_batch_size: 8
- 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: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.0483        | 0.0967 | 50   | 0.9260          |
| 0.8577        | 0.1934 | 100  | 0.8202          |
| 0.7996        | 0.2901 | 150  | 0.7895          |
| 0.7802        | 0.3868 | 200  | 0.7784          |
| 0.7671        | 0.4836 | 250  | 0.7721          |
| 0.761         | 0.5803 | 300  | 0.7688          |
| 0.7587        | 0.6770 | 350  | 0.7663          |
| 0.7529        | 0.7737 | 400  | 0.7637          |
| 0.7562        | 0.8704 | 450  | 0.7616          |
| 0.7507        | 0.9671 | 500  | 0.7602          |
| 0.7274        | 1.0638 | 550  | 0.7589          |
| 0.7422        | 1.1605 | 600  | 0.7574          |
| 0.735         | 1.2573 | 650  | 0.7571          |
| 0.7367        | 1.3540 | 700  | 0.7555          |
| 0.7471        | 1.4507 | 750  | 0.7549          |
| 0.7404        | 1.5474 | 800  | 0.7541          |
| 0.742         | 1.6441 | 850  | 0.7533          |
| 0.7385        | 1.7408 | 900  | 0.7530          |
| 0.7352        | 1.8375 | 950  | 0.7525          |
| 0.7323        | 1.9342 | 1000 | 0.7516          |
| 0.7328        | 2.0309 | 1050 | 0.7515          |
| 0.7264        | 2.1277 | 1100 | 0.7510          |
| 0.704         | 2.2244 | 1150 | 0.7505          |
| 0.7242        | 2.3211 | 1200 | 0.7510          |
| 0.7203        | 2.4178 | 1250 | 0.7502          |
| 0.7285        | 2.5145 | 1300 | 0.7499          |
| 0.7192        | 2.6112 | 1350 | 0.7502          |
| 0.7204        | 2.7079 | 1400 | 0.7497          |


### Framework versions

- PEFT 0.12.0
- Transformers 4.42.3
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.19.1