---
library_name: peft
tags:
- trl
- sft
- generated_from_trainer
datasets:
- kpriyanshu256/databricks-dolly-15k-hi
base_model: NousResearch/Llama-2-7b-hf
model-index:
- name: llama2-7b-int4-dolly-15k-hindi-flash-attention2-w-packing
  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. -->

# llama2-7b-int4-dolly-15k-hindi-flash-attention2-w-packing

This model is a fine-tuned version of [NousResearch/Llama-2-7b-hf](https://huggingface.co/NousResearch/Llama-2-7b-hf) on the [kpriyanshu256/databricks-dolly-15k-hi](https://huggingface.co/datasets/kpriyanshu256/databricks-dolly-15k-hi) dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5537

## 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: 0.0002
- train_batch_size: 6
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.6986        | 0.16  | 100  | 0.6539          |
| 0.6441        | 0.31  | 200  | 0.6297          |
| 0.6231        | 0.47  | 300  | 0.6146          |
| 0.6066        | 0.62  | 400  | 0.6020          |
| 0.5922        | 0.78  | 500  | 0.5930          |
| 0.6023        | 0.94  | 600  | 0.5847          |
| 0.5618        | 1.09  | 700  | 0.5792          |
| 0.5496        | 1.25  | 800  | 0.5742          |
| 0.5428        | 1.41  | 900  | 0.5699          |
| 0.5336        | 1.56  | 1000 | 0.5643          |
| 0.5331        | 1.72  | 1100 | 0.5605          |
| 0.5255        | 1.88  | 1200 | 0.5574          |
| 0.5155        | 2.03  | 1300 | 0.5581          |
| 0.4851        | 2.19  | 1400 | 0.5565          |
| 0.4831        | 2.34  | 1500 | 0.5563          |
| 0.489         | 2.5   | 1600 | 0.5545          |
| 0.4901        | 2.66  | 1700 | 0.5540          |
| 0.4863        | 2.81  | 1800 | 0.5537          |
| 0.479         | 2.97  | 1900 | 0.5537          |


### Framework versions

- PEFT 0.7.2.dev0
- Transformers 4.37.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.16.2.dev0
- Tokenizers 0.15.0