File size: 2,144 Bytes
df435ab 1fb444b ae87025 aa5b7a3 df435ab ae87025 df435ab ae87025 df435ab aa5b7a3 |
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 |
---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- winglian/no_robots_rlhf
- HuggingFaceH4/no_robots
base_model: teknium/OpenHermes-2.5-Mistral-7B
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)
# openhermes-2_5-dpo-no-robots
This model is a RL fine-tuned version of [teknium/OpenHermes-2.5-Mistral-7B](https://huggingface.co/teknium/OpenHermes-2.5-Mistral-7B) on a preference dataset derived from HuggingFace's [no robots dataset](https://huggingface.co/datasets/HuggingFaceH4/no_robots) using DPO.
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-07
- train_batch_size: 2
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- total_eval_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 20
- training_steps: 408
### Training results
### Framework versions
- Transformers 4.35.2
- Pytorch 2.0.1+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
# [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_openaccess-ai-collective__openhermes-2_5-dpo-no-robots)
| Metric |Value|
|---------------------------------|----:|
|Avg. |66.40|
|AI2 Reasoning Challenge (25-Shot)|64.93|
|HellaSwag (10-Shot) |84.30|
|MMLU (5-Shot) |63.86|
|TruthfulQA (0-shot) |52.12|
|Winogrande (5-shot) |77.90|
|GSM8k (5-shot) |55.27|
|