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---
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
---
# 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.
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.
## 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. |