---
library_name: peft
license: mit
base_model: microsoft/Phi-3-mini-128k-instruct
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: phi-3-mini-sft-indicqa-hindi-v0.1
  results: []
datasets:
- sepiatone/ai4bharat-IndicQA-hi-202410
- ai4bharat/IndicQA
---

<!-- 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-3-mini-sft-indicqa-hindi-v0.1**



### model description

this model is a fine-tuned version of [microsoft/Phi-3-mini-128k-instruct](https://huggingface.co/microsoft/Phi-3-mini-128k-instruct) on the dataset [
ai4bharat-IndicQA-hi-202410](https://huggingface.co/datasets/sepiatone/ai4bharat-IndicQA-hi-202410).

prepared by [@sepiatone](https://github.com/sepiatone).

### intended uses & limitations

intended for an educational and non-commercial purpose.

### training procedure

#### training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.0002
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 1
- mixed_precision_training: Native AMP


#### library versions

- PEFT 0.13.2
- Transformers 4.44.2
- Pytorch 2.5.0+cu121
- Datasets 3.0.2
- Tokenizers 0.19.1