File size: 3,638 Bytes
1c640a0 e092078 1c640a0 e092078 1c640a0 e092078 1c640a0 581aba3 1c640a0 581aba3 1c640a0 e092078 1c640a0 e092078 1c640a0 e092078 8e7266b 1c640a0 e092078 5a37b3d |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 |
---
tags:
- generated_from_trainer
model-index:
- name: no_robots-alpaca
results: []
license: cc-by-nc-4.0
---
<!-- 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)
# no_robots-alpaca
This lora was trained with [Doctor-Shotgun/no-robots-sharegpt](https://huggingface.co/datasets/Doctor-Shotgun/no-robots-sharegpt) dataset on [TheBloke/Llama-2-13B-fp16](https://huggingface.co/TheBloke/Llama-2-13B-fp16).
It achieves the following results on the evaluation set:
- Loss: 1.6087
## Model description
The LoRA was trained on [Doctor-Shotgun/no-robots-sharegpt](https://huggingface.co/datasets/Doctor-Shotgun/no-robots-sharegpt), a ShareGPT converted dataset from the OG [HuggingFaceH4/no_robots](https://huggingface.co/datasets/HuggingFaceH4/no_robots) but with Alpaca prompting.
## Prompt template: Alpaca
```
Below is an instruction that describes a task. Write a response that appropriately completes the request.
### Instruction:
{prompt}
### Response:
```
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.00065
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- lr_scheduler_warmup_steps: 10
- num_epochs: 2
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.5523 | 0.0 | 1 | 1.5476 |
| 1.2139 | 0.1 | 42 | 1.5008 |
| 1.6348 | 0.2 | 84 | 1.4968 |
| 1.6498 | 0.3 | 126 | 1.4962 |
| 1.5645 | 0.4 | 168 | 1.4983 |
| 1.6487 | 0.5 | 210 | 1.4981 |
| 1.6147 | 0.6 | 252 | 1.4965 |
| 1.3048 | 0.7 | 294 | 1.4973 |
| 1.6205 | 0.8 | 336 | 1.5007 |
| 1.6045 | 0.9 | 378 | 1.5003 |
| 1.5781 | 1.0 | 420 | 1.5013 |
| 1.4807 | 1.09 | 462 | 1.5492 |
| 1.0541 | 1.19 | 504 | 1.5596 |
| 1.2337 | 1.29 | 546 | 1.5789 |
| 0.9719 | 1.39 | 588 | 1.5859 |
| 1.2189 | 1.49 | 630 | 1.5959 |
| 1.2566 | 1.59 | 672 | 1.5968 |
| 0.7049 | 1.69 | 714 | 1.5987 |
| 1.2133 | 1.79 | 756 | 1.5907 |
| 1.0327 | 1.89 | 798 | 1.6087 |
### Framework versions
- Transformers 4.34.1
- Pytorch 2.0.1+cu117
- Datasets 2.14.6
- Tokenizers 0.14.1
If you want to support me, you can [here](https://ko-fi.com/undiai).
# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_Undi95__Llama2-13B-no_robots-alpaca-lora)
| Metric | Value |
|-----------------------|---------------------------|
| Avg. | 46.55 |
| ARC (25-shot) | 58.87 |
| HellaSwag (10-shot) | 82.43 |
| MMLU (5-shot) | 53.11 |
| TruthfulQA (0-shot) | 40.46 |
| Winogrande (5-shot) | 75.3 |
| GSM8K (5-shot) | 6.44 |
| DROP (3-shot) | 9.26 |
|