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metadata
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

distilgpt2-nepali-patrakar-qa

This model is a fine-tuned version of 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

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; 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