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---
license: llama2
library_name: peft
tags:
- generated_from_trainer
base_model: meta-llama/Llama-2-7b-hf
model-index:
- name: hindi-llama
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. -->
# hindi-llama
This model is a fine-tuned version of [meta-llama/Llama-2-7b-hf](https://huggingface.co/meta-llama/Llama-2-7b-hf) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1632
## 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: 2e-05
- train_batch_size: 1
- eval_batch_size: 1
- 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: 1
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:-----:|:---------------:|
| 1.5858 | 0.0188 | 1000 | 1.4610 |
| 1.3662 | 0.0375 | 2000 | 1.3469 |
| 1.3174 | 0.0563 | 3000 | 1.3143 |
| 1.3003 | 0.0750 | 4000 | 1.2895 |
| 1.2931 | 0.0938 | 5000 | 1.2762 |
| 1.2786 | 0.1125 | 6000 | 1.2649 |
| 1.2541 | 0.1313 | 7000 | 1.2556 |
| 1.2594 | 0.1500 | 8000 | 1.2481 |
| 1.2523 | 0.1688 | 9000 | 1.2415 |
| 1.244 | 0.1876 | 10000 | 1.2348 |
| 1.2274 | 0.2063 | 11000 | 1.2309 |
| 1.2167 | 0.2251 | 12000 | 1.2257 |
| 1.2359 | 0.2438 | 13000 | 1.2225 |
| 1.2156 | 0.2626 | 14000 | 1.2191 |
| 1.204 | 0.2813 | 15000 | 1.2146 |
| 1.2203 | 0.3001 | 16000 | 1.2109 |
| 1.2016 | 0.3188 | 17000 | 1.2094 |
| 1.2117 | 0.3376 | 18000 | 1.2057 |
| 1.2183 | 0.3563 | 19000 | 1.2038 |
| 1.2108 | 0.3751 | 20000 | 1.2005 |
| 1.2153 | 0.3939 | 21000 | 1.1981 |
| 1.189 | 0.4126 | 22000 | 1.1968 |
| 1.1857 | 0.4314 | 23000 | 1.1947 |
| 1.1688 | 0.4501 | 24000 | 1.1914 |
| 1.2028 | 0.4689 | 25000 | 1.1907 |
| 1.1916 | 0.4876 | 26000 | 1.1893 |
| 1.1797 | 0.5064 | 27000 | 1.1873 |
| 1.1897 | 0.5251 | 28000 | 1.1848 |
| 1.1817 | 0.5439 | 29000 | 1.1837 |
| 1.1837 | 0.5627 | 30000 | 1.1826 |
| 1.1889 | 0.5814 | 31000 | 1.1808 |
| 1.1754 | 0.6002 | 32000 | 1.1798 |
| 1.1868 | 0.6189 | 33000 | 1.1790 |
| 1.1792 | 0.6377 | 34000 | 1.1780 |
| 1.1772 | 0.6564 | 35000 | 1.1766 |
| 1.1763 | 0.6752 | 36000 | 1.1755 |
| 1.1719 | 0.6939 | 37000 | 1.1746 |
| 1.1804 | 0.7127 | 38000 | 1.1724 |
| 1.1763 | 0.7314 | 39000 | 1.1717 |
| 1.1715 | 0.7502 | 40000 | 1.1717 |
| 1.1732 | 0.7690 | 41000 | 1.1701 |
| 1.1808 | 0.7877 | 42000 | 1.1692 |
| 1.1713 | 0.8065 | 43000 | 1.1688 |
| 1.175 | 0.8252 | 44000 | 1.1678 |
| 1.1604 | 0.8440 | 45000 | 1.1668 |
| 1.1619 | 0.8627 | 46000 | 1.1658 |
| 1.1686 | 0.8815 | 47000 | 1.1650 |
| 1.1541 | 0.9002 | 48000 | 1.1647 |
| 1.1776 | 0.9190 | 49000 | 1.1641 |
| 1.1675 | 0.9378 | 50000 | 1.1640 |
| 1.1727 | 0.9565 | 51000 | 1.1636 |
| 1.1566 | 0.9753 | 52000 | 1.1633 |
| 1.1657 | 0.9940 | 53000 | 1.1632 |
### Framework versions
- PEFT 0.11.1
- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.19.2
- Tokenizers 0.19.1 |