---
license: apache-2.0
base_model: Sakonii/distilgpt2-nepali
tags:
- generated_from_trainer
widget:
- text: 'नेपाली राजनीतिमा युवा पिढीको भूमिका के हो? '
  example_title: Example 1
- text: 'नेपालको ग्रामीण र शहरी क्षेत्रमा स्वास्थ्य सेवा कस्तो छ? '
  example_title: Example 2
- text: 'नेपाली राजनीतिमा युवा पिढीको भूमिका के हो? '
  example_title: Example 3
model-index:
- name: distilgpt2-nepali-qa
  results: []
language:
- ne
---

<!-- 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. -->

# distilgpt2-nepali-patrakar-qa

This model is a fine-tuned version of [Sakonii/distilgpt2-nepali](https://huggingface.co/Sakonii/distilgpt2-nepali) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 3.9077

## Model description

Refer to original [distilgpt2](https://huggingface.co/distilgpt2)

## Intended uses & limitations

This marginally fine-tuned model can be used for Nepali text generation and possibly question answering and intends to be fine-tuned on Nepali language focused generative downstream task. 
The language model being trained on a data with texts grouped to a block size of 512, it handles text sequence up to 512 tokens.

## Training procedure

The model is trained with the same configuration as the original [distilgpt2](https://huggingface.co/distilgpt2); but with 512 tokens per instance, 72 instances per batch, and around 34.14K training steps (excluding the pre-training with CLM Objective).

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 72
- eval_batch_size: 72
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 4.1278        | 1.0   | 6829  | 4.0184          |
| 3.9461        | 2.0   | 13658 | 3.9630          |
| 3.8268        | 3.0   | 20487 | 3.9319          |
| 3.7978        | 4.0   | 27316 | 3.9140          |
| 3.7949        | 5.0   | 34145 | 3.9077          |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3