---
base_model: meta-llama/Llama-2-13b-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-2-13b-hf](https://huggingface.co/meta-llama/Llama-2-13b-hf) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5407

## 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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 300
- num_epochs: 1

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.8973        | 0.03  | 20   | 0.7029          |
| 0.6828        | 0.06  | 40   | 0.6521          |
| 0.6521        | 0.09  | 60   | 0.6199          |
| 0.7857        | 0.11  | 80   | 0.6066          |
| 0.6208        | 0.14  | 100  | 0.6063          |
| 0.6805        | 0.17  | 120  | 0.5969          |
| 0.5928        | 0.2   | 140  | 0.5989          |
| 0.715         | 0.23  | 160  | 0.5844          |
| 0.5647        | 0.26  | 180  | 0.5979          |
| 0.6778        | 0.29  | 200  | 0.5889          |
| 0.5907        | 0.31  | 220  | 0.5772          |
| 0.5536        | 0.34  | 240  | 0.5917          |
| 0.7422        | 0.37  | 260  | 0.6781          |
| 0.6328        | 0.4   | 280  | 0.5785          |
| 0.5705        | 0.43  | 300  | 0.5720          |
| 0.6124        | 0.46  | 320  | 0.5753          |
| 0.4735        | 0.49  | 340  | 0.6203          |
| 0.4602        | 0.52  | 360  | 0.5772          |
| 0.8571        | 0.54  | 380  | 0.5750          |
| 0.5504        | 0.57  | 400  | 0.6040          |
| 0.6307        | 0.6   | 420  | 0.5796          |
| 0.4782        | 0.63  | 440  | 0.5639          |
| 0.4159        | 0.66  | 460  | 0.5689          |
| 0.6393        | 0.69  | 480  | 0.5661          |
| 0.8243        | 0.72  | 500  | 0.5698          |
| 0.4744        | 0.74  | 520  | 0.5536          |
| 0.4395        | 0.77  | 540  | 0.5536          |
| 0.543         | 0.8   | 560  | 0.5493          |
| 0.4451        | 0.83  | 580  | 0.5421          |
| 0.5384        | 0.86  | 600  | 0.5467          |
| 0.4438        | 0.89  | 620  | 0.5379          |
| 0.4168        | 0.92  | 640  | 0.5398          |
| 0.469         | 0.94  | 660  | 0.5402          |
| 0.6766        | 0.97  | 680  | 0.5407          |


### Framework versions

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