transformers llama text-generation generated_from_trainer base_model:meta-llama/Llama-2-13b-hf autotrain_compatible endpoints_compatible text-generation-inference 4-bit bitsandbytes region:us
---
base_model: meta-llama/Llama-2-13b-hf
tags:
- generated_from_trainer
model-index:
- name: qlora-out
  results: []
---

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[<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: 0.5302

## 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: 2
- total_train_batch_size: 2
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- num_epochs: 1

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.7438        | 0.01  | 20   | 0.6827          |
| 0.8518        | 0.01  | 40   | 0.6707          |
| 0.6798        | 0.02  | 60   | 0.6511          |
| 0.7868        | 0.03  | 80   | 0.6231          |
| 0.8218        | 0.04  | 100  | 0.6232          |
| 0.6862        | 0.04  | 120  | 0.6324          |
| 0.4989        | 0.05  | 140  | 0.6007          |
| 0.6064        | 0.06  | 160  | 0.6127          |
| 0.5355        | 0.06  | 180  | 0.6297          |
| 0.6274        | 0.07  | 200  | 0.6211          |
| 0.5512        | 0.08  | 220  | 0.6290          |
| 0.727         | 0.08  | 240  | 0.6028          |
| 0.5253        | 0.09  | 260  | 0.5971          |
| 0.7679        | 0.1   | 280  | 0.5908          |
| 0.4804        | 0.11  | 300  | 0.6154          |
| 0.5801        | 0.11  | 320  | 0.5968          |
| 0.3603        | 0.12  | 340  | 0.7127          |
| 0.5948        | 0.13  | 360  | 0.5911          |
| 0.7988        | 0.13  | 380  | 0.6060          |
| 0.6002        | 0.14  | 400  | 0.6303          |
| 0.5522        | 0.15  | 420  | 0.6124          |
| 0.558         | 0.16  | 440  | 0.6061          |
| 0.393         | 0.16  | 460  | 0.6050          |
| 0.739         | 0.17  | 480  | 0.5977          |
| 0.6462        | 0.18  | 500  | 0.5904          |
| 0.5305        | 0.18  | 520  | 0.5852          |
| 0.4749        | 0.19  | 540  | 0.5974          |
| 0.832         | 0.2   | 560  | 0.5918          |
| 0.7155        | 0.21  | 580  | 0.5857          |
| 0.7374        | 0.21  | 600  | 0.6092          |
| 1.2165        | 0.22  | 620  | 0.6071          |
| 0.4901        | 0.23  | 640  | 0.5908          |
| 0.4585        | 0.23  | 660  | 0.6041          |
| 0.6474        | 0.24  | 680  | 0.5984          |
| 0.4136        | 0.25  | 700  | 0.5860          |
| 0.602         | 0.25  | 720  | 0.6251          |
| 0.405         | 0.26  | 740  | 0.6182          |
| 0.5059        | 0.27  | 760  | 0.5894          |
| 0.4249        | 0.28  | 780  | 0.5800          |
| 0.4847        | 0.28  | 800  | 0.5805          |
| 0.4709        | 0.29  | 820  | 0.6140          |
| 0.4279        | 0.3   | 840  | 0.5877          |
| 0.7142        | 0.3   | 860  | 0.5801          |
| 1.0536        | 0.31  | 880  | 0.6102          |
| 0.694         | 0.32  | 900  | 0.5812          |
| 0.5034        | 0.33  | 920  | 0.5833          |
| 0.4208        | 0.33  | 940  | 0.5803          |
| 0.5917        | 0.34  | 960  | 0.5756          |
| 0.4655        | 0.35  | 980  | 0.5706          |
| 0.4274        | 0.35  | 1000 | 0.5675          |
| 0.3711        | 0.36  | 1020 | 0.5791          |
| 0.6792        | 0.37  | 1040 | 0.5773          |
| 0.3607        | 0.38  | 1060 | 0.5838          |
| 0.5336        | 0.38  | 1080 | 0.5744          |
| 0.5509        | 0.39  | 1100 | 0.5854          |
| 0.2759        | 0.4   | 1120 | 0.5675          |
| 0.5058        | 0.4   | 1140 | 0.5790          |
| 0.4446        | 0.41  | 1160 | 0.5893          |
| 0.4757        | 0.42  | 1180 | 0.5764          |
| 0.4153        | 0.42  | 1200 | 0.5707          |
| 0.5369        | 0.43  | 1220 | 0.5729          |
| 0.4785        | 0.44  | 1240 | 0.5735          |
| 0.4335        | 0.45  | 1260 | 0.5821          |
| 0.5452        | 0.45  | 1280 | 0.5621          |
| 0.3461        | 0.46  | 1300 | 0.5615          |
| 0.5579        | 0.47  | 1320 | 0.5769          |
| 0.6048        | 0.47  | 1340 | 0.5855          |
| 0.6253        | 0.48  | 1360 | 0.5590          |
| 0.5084        | 0.49  | 1380 | 0.5822          |
| 0.3838        | 0.5   | 1400 | 0.5604          |
| 0.667         | 0.5   | 1420 | 0.5622          |
| 0.681         | 0.51  | 1440 | 0.5632          |
| 0.3593        | 0.52  | 1460 | 0.5578          |
| 0.4509        | 0.52  | 1480 | 0.5609          |
| 0.4752        | 0.53  | 1500 | 0.5494          |
| 0.3152        | 0.54  | 1520 | 0.5541          |
| 0.3699        | 0.55  | 1540 | 0.5449          |
| 0.3009        | 0.55  | 1560 | 0.5656          |
| 0.2867        | 0.56  | 1580 | 0.5499          |
| 0.7261        | 0.57  | 1600 | 0.5490          |
| 0.5149        | 0.57  | 1620 | 0.5565          |
| 0.473         | 0.58  | 1640 | 0.5445          |
| 0.9732        | 0.59  | 1660 | 0.5505          |
| 0.9606        | 0.59  | 1680 | 0.5471          |
| 0.2714        | 0.6   | 1700 | 0.5651          |
| 0.4927        | 0.61  | 1720 | 0.5527          |
| 0.6928        | 0.62  | 1740 | 0.5433          |
| 0.3776        | 0.62  | 1760 | 0.5507          |
| 0.4636        | 0.63  | 1780 | 0.5443          |
| 0.43          | 0.64  | 1800 | 0.5527          |
| 0.5656        | 0.64  | 1820 | 0.5478          |
| 0.729         | 0.65  | 1840 | 0.5542          |
| 0.4355        | 0.66  | 1860 | 0.5411          |
| 0.377         | 0.67  | 1880 | 0.5426          |
| 0.5345        | 0.67  | 1900 | 0.5434          |
| 0.4042        | 0.68  | 1920 | 0.5383          |
| 0.3676        | 0.69  | 1940 | 0.5372          |
| 0.4758        | 0.69  | 1960 | 0.5411          |
| 0.4919        | 0.7   | 1980 | 0.5353          |
| 0.2312        | 0.71  | 2000 | 0.5351          |
| 0.7224        | 0.71  | 2020 | 0.5364          |
| 0.3617        | 0.72  | 2040 | 0.5357          |
| 0.8601        | 0.73  | 2060 | 0.5402          |
| 0.3218        | 0.74  | 2080 | 0.5309          |
| 0.3611        | 0.74  | 2100 | 0.5412          |
| 0.4466        | 0.75  | 2120 | 0.5432          |
| 0.5551        | 0.76  | 2140 | 0.5345          |
| 0.4047        | 0.76  | 2160 | 0.5321          |
| 0.4624        | 0.77  | 2180 | 0.5357          |
| 0.5704        | 0.78  | 2200 | 0.5325          |
| 0.715         | 0.79  | 2220 | 0.5313          |
| 0.4913        | 0.79  | 2240 | 0.5300          |
| 0.3605        | 0.8   | 2260 | 0.5294          |
| 0.234         | 0.81  | 2280 | 0.5318          |
| 0.6128        | 0.81  | 2300 | 0.5365          |
| 0.236         | 0.82  | 2320 | 0.5342          |
| 0.3503        | 0.83  | 2340 | 0.5348          |
| 0.4874        | 0.84  | 2360 | 0.5313          |
| 0.5999        | 0.84  | 2380 | 0.5312          |
| 0.2757        | 0.85  | 2400 | 0.5292          |
| 0.322         | 0.86  | 2420 | 0.5299          |
| 0.4368        | 0.86  | 2440 | 0.5318          |
| 0.318         | 0.87  | 2460 | 0.5319          |
| 0.7192        | 0.88  | 2480 | 0.5307          |
| 0.3465        | 0.88  | 2500 | 0.5315          |
| 0.4098        | 0.89  | 2520 | 0.5312          |
| 0.682         | 0.9   | 2540 | 0.5308          |
| 1.4551        | 0.91  | 2560 | 0.5310          |
| 0.4396        | 0.91  | 2580 | 0.5301          |
| 0.5932        | 0.92  | 2600 | 0.5298          |
| 0.3978        | 0.93  | 2620 | 0.5292          |
| 0.2823        | 0.93  | 2640 | 0.5296          |
| 0.4293        | 0.94  | 2660 | 0.5294          |
| 0.4646        | 0.95  | 2680 | 0.5296          |
| 0.8203        | 0.96  | 2700 | 0.5295          |
| 0.351         | 0.96  | 2720 | 0.5299          |
| 0.328         | 0.97  | 2740 | 0.5292          |
| 0.3347        | 0.98  | 2760 | 0.5302          |
| 0.2608        | 0.98  | 2780 | 0.5296          |
| 0.4274        | 0.99  | 2800 | 0.5294          |
| 0.3349        | 1.0   | 2820 | 0.5302          |


### Framework versions

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