---
library_name: transformers
license: mit
base_model: gpt2
tags:
- generated_from_trainer
datasets:
- rahul7star/hindi-poetry
language:
- hi
model-index:
- name: hindi_poetry_language_model
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# hindi_poetry_language_model

This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on an known dataset.
https://huggingface.co/datasets/rahul7star/hindi-poetry
It achieves the following results on the evaluation set:
- Loss: 0.4038

## Model description

Model is trained based on small set https://huggingface.co/datasets/rahul7star/hindi-poetry

## 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: 5e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| No log        | 1.0   | 3    | 0.4765          |
| No log        | 2.0   | 6    | 0.4183          |
| No log        | 3.0   | 9    | 0.4038          |


### Framework versions

- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0
- 
### Citation

```
@misc{hindipoetry,
  author = {Rahul7star},
  title = {Hindi Poetry},
  year = {2025},
  publisher = {Hugging Face},
  journal = {Hugging Face repository},
  url = {\url{https://huggingface.co/spaces/rahul7star}}
}

```