|
--- |
|
license: cc-by-nc-nd-4.0 |
|
tags: |
|
- generated_from_trainer |
|
model-index: |
|
- name: UNA-TheBeagle-7b-v1 |
|
results: [] |
|
datasets: |
|
- jondurbin/bagel-v0.3 |
|
library_name: transformers |
|
--- |
|
-- In the Love Memory of my "LoLa" -- |
|
|
|
# UNA-TheBeagle-7b-v1 |
|
TheBeagle, a model of 7B parameters trained on The Bagel dataset. DPO & UNA applied over a set of curated DPO Pairs. |
|
|
|
- Scored #1 on the HF Leaderboard, dramatic scores!!! 73 ARC, and very well balanced! |
|
|
|
The dataset was generated using the original bagel code, including the decontamination step. |
|
|
|
As base model, we used the latest Intel's neural-chat model. |
|
|
|
It performs very good in many tasks, but its always better that you play with it by yourself. |
|
|
|
![TheBeagle](https://huggingface.co/fblgit/UNA-TheBeagle-7b-v1/resolve/main/TheBeagle.png) |
|
|
|
## Evaluations |
|
|
|
Ran with VLLM so expect them to dont be exactly as the one's shown in the board, but not too far :) |
|
|
|
``` |
|
vllm (pretrained=fblgit/UNA-TheBeagle-7b-v1,dtype=auto,tensor_parallel_size=1,gpu_memory_utilization=0.8,data_parallel_size=8,trust_remote_code=True), gen_kwargs: (None), limit: None, num_fewshot: None, batch_size: 32 |
|
| Tasks |Version| Filter |n-shot| Metric |Value | |Stderr| |
|
|--------------|-------|----------|-----:|-----------|-----:|---|-----:| |
|
|arc_challenge |Yaml |none | 25|acc |0.7090|± |0.0133| |
|
| | |none | 25|acc_norm |0.7329|± |0.0129| |
|
|gsm8k |Yaml |get-answer| 5|exact_match|0.7210|± |0.0124| |
|
|hellaswag |Yaml |none | 10|acc |0.7202|± |0.0045| |
|
| | |none | 10|acc_norm |0.8792|± |0.0033| |
|
|truthfulqa_mc2|Yaml |none | 0|acc |0.7062|± |0.0151| |
|
|winogrande |Yaml |none | 5|acc |0.8366|± |0.0104| |
|
``` |
|
|
|
## UNA Details |
|
|
|
For this release, we only applied UNA thru the perceptrons. It was done at a 3.5e-7 speed, and the training loop code is also the original one of the bagel and transformers-4.35.2-UNA |
|
|
|
## Prompt |
|
|
|
Im not entirely sure of it, as we used the vanilla version of the bagel training code. But a good model should be able to generalize with different prompt formats, so feel free to give it a shot. |
|
|
|
## Citations |
|
|
|
Remember if you use UNA's models, cite it in your model card. |
|
|
|
## Limitations |
|
Not for commercial use, and only for academic & research purposes. |