---
base_model: meta-llama/Llama-2-7b-hf
tags:
- generated_from_trainer
model-index:
- name: qlora-out
  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. -->

[<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl)
# qlora-out

This model is a fine-tuned version of [meta-llama/Llama-2-7b-hf](https://huggingface.co/meta-llama/Llama-2-7b-hf) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5703

## 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: 0.0004
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- num_epochs: 2

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.8756        | 0.06  | 20   | 0.7111          |
| 0.9058        | 0.11  | 40   | 0.6764          |
| 0.7526        | 0.17  | 60   | 0.6669          |
| 0.6926        | 0.23  | 80   | 0.6363          |
| 0.6731        | 0.28  | 100  | 0.6187          |
| 0.647         | 0.34  | 120  | 0.6162          |
| 0.6219        | 0.4   | 140  | 0.6041          |
| 0.5781        | 0.45  | 160  | 0.5937          |
| 0.6346        | 0.51  | 180  | 0.6006          |
| 0.7663        | 0.57  | 200  | 0.5926          |
| 0.5864        | 0.62  | 220  | 0.5866          |
| 0.5943        | 0.68  | 240  | 0.5756          |
| 0.5029        | 0.74  | 260  | 0.5733          |
| 0.5482        | 0.79  | 280  | 0.5712          |
| 0.5413        | 0.85  | 300  | 0.5820          |
| 0.657         | 0.91  | 320  | 0.5696          |
| 0.506         | 0.96  | 340  | 0.5839          |
| 0.4804        | 1.02  | 360  | 0.5803          |
| 0.5095        | 1.08  | 380  | 0.5974          |
| 0.4404        | 1.13  | 400  | 0.5746          |
| 0.3869        | 1.19  | 420  | 0.5740          |
| 0.4129        | 1.25  | 440  | 0.5777          |
| 0.4209        | 1.3   | 460  | 0.5825          |
| 0.4014        | 1.36  | 480  | 0.5742          |
| 0.3333        | 1.42  | 500  | 0.5851          |
| 0.5041        | 1.47  | 520  | 0.5798          |
| 0.5528        | 1.53  | 540  | 0.5631          |
| 0.4372        | 1.59  | 560  | 0.5747          |
| 0.3901        | 1.64  | 580  | 0.5625          |
| 0.5271        | 1.7   | 600  | 0.5746          |
| 0.4283        | 1.76  | 620  | 0.5662          |
| 0.4336        | 1.81  | 640  | 0.5652          |
| 0.3534        | 1.87  | 660  | 0.5697          |
| 0.4728        | 1.93  | 680  | 0.5713          |
| 0.5159        | 1.98  | 700  | 0.5703          |


### Framework versions

- Transformers 4.34.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1