---
base_model: microsoft/Phi-3-mini-4k-instruct
library_name: peft
license: mit
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: question-generator
  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

This model is a fine-tuned version of [microsoft/Phi-3-mini-4k-instruct](https://huggingface.co/microsoft/Phi-3-mini-4k-instruct) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4475

## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 1.8852        | 0.08  | 50   | 1.7072          |
| 1.6036        | 0.16  | 100  | 1.4856          |
| 1.5186        | 0.24  | 150  | 1.4662          |
| 1.4822        | 0.32  | 200  | 1.4603          |
| 1.5035        | 0.4   | 250  | 1.4578          |
| 1.4813        | 0.48  | 300  | 1.4558          |
| 1.4878        | 0.56  | 350  | 1.4534          |
| 1.4765        | 0.64  | 400  | 1.4523          |
| 1.4803        | 0.72  | 450  | 1.4485          |
| 1.4925        | 0.8   | 500  | 1.4478          |
| 1.49          | 0.88  | 550  | 1.4467          |
| 1.4888        | 0.96  | 600  | 1.4461          |
| 1.4732        | 1.04  | 650  | 1.4470          |
| 1.4677        | 1.12  | 700  | 1.4476          |
| 1.4402        | 1.2   | 750  | 1.4475          |


### Framework versions

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