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---
language:
- pt
- en
license: apache-2.0
model-index:
- name: open-cabrita3b
results:
- task:
type: text-generation
name: Text Generation
dataset:
name: AI2 Reasoning Challenge (25-Shot)
type: ai2_arc
config: ARC-Challenge
split: test
args:
num_few_shot: 25
metrics:
- type: acc_norm
value: 33.79
name: normalized accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=22h/open-cabrita3b
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: HellaSwag (10-Shot)
type: hellaswag
split: validation
args:
num_few_shot: 10
metrics:
- type: acc_norm
value: 55.35
name: normalized accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=22h/open-cabrita3b
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: MMLU (5-Shot)
type: cais/mmlu
config: all
split: test
args:
num_few_shot: 5
metrics:
- type: acc
value: 25.16
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=22h/open-cabrita3b
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: TruthfulQA (0-shot)
type: truthful_qa
config: multiple_choice
split: validation
args:
num_few_shot: 0
metrics:
- type: mc2
value: 38.5
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=22h/open-cabrita3b
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: Winogrande (5-shot)
type: winogrande
config: winogrande_xl
split: validation
args:
num_few_shot: 5
metrics:
- type: acc
value: 59.43
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=22h/open-cabrita3b
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: GSM8k (5-shot)
type: gsm8k
config: main
split: test
args:
num_few_shot: 5
metrics:
- type: acc
value: 0.99
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=22h/open-cabrita3b
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: ENEM Challenge (No Images)
type: eduagarcia/enem_challenge
split: train
args:
num_few_shot: 3
metrics:
- type: acc
value: 17.98
name: accuracy
source:
url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=22h/open-cabrita3b
name: Open Portuguese LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: BLUEX (No Images)
type: eduagarcia-temp/BLUEX_without_images
split: train
args:
num_few_shot: 3
metrics:
- type: acc
value: 21.14
name: accuracy
source:
url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=22h/open-cabrita3b
name: Open Portuguese LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: OAB Exams
type: eduagarcia/oab_exams
split: train
args:
num_few_shot: 3
metrics:
- type: acc
value: 22.69
name: accuracy
source:
url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=22h/open-cabrita3b
name: Open Portuguese LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: Assin2 RTE
type: assin2
split: test
args:
num_few_shot: 15
metrics:
- type: f1_macro
value: 43.01
name: f1-macro
- type: pearson
value: 8.92
name: pearson
source:
url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=22h/open-cabrita3b
name: Open Portuguese LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: FaQuAD NLI
type: ruanchaves/faquad-nli
split: test
args:
num_few_shot: 15
metrics:
- type: f1_macro
value: 43.97
name: f1-macro
source:
url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=22h/open-cabrita3b
name: Open Portuguese LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: HateBR Binary
type: eduagarcia/portuguese_benchmark
split: test
args:
num_few_shot: 25
metrics:
- type: f1_macro
value: 50.46
name: f1-macro
- type: f1_macro
value: 41.19
name: f1-macro
source:
url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=22h/open-cabrita3b
name: Open Portuguese LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: tweetSentBR
type: eduagarcia-temp/tweetsentbr
split: test
args:
num_few_shot: 25
metrics:
- type: f1_macro
value: 47.96
name: f1-macro
source:
url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=22h/open-cabrita3b
name: Open Portuguese LLM Leaderboard
---
The Cabrita model is a collection of continued pre-trained and tokenizer-adapted models for the Portuguese language.
This artifact is the 3 billion size variant.
The weights were initially obtained from the open-llama project (https://github.com/openlm-research/open_llama) in the
open_llama_3b option.
```
@misc{larcher2023cabrita,
title={Cabrita: closing the gap for foreign languages},
author={Celio Larcher and Marcos Piau and Paulo Finardi and Pedro Gengo and Piero Esposito and Vinicius Caridá},
year={2023},
eprint={2308.11878},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
```
# [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_22h__open-cabrita3b)
| Metric |Value|
|---------------------------------|----:|
|Avg. |35.54|
|AI2 Reasoning Challenge (25-Shot)|33.79|
|HellaSwag (10-Shot) |55.35|
|MMLU (5-Shot) |25.16|
|TruthfulQA (0-shot) |38.50|
|Winogrande (5-shot) |59.43|
|GSM8k (5-shot) | 0.99|
# [Open Portuguese LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard)
Detailed results can be found [here](https://huggingface.co/datasets/eduagarcia-temp/llm_pt_leaderboard_raw_results/tree/main/22h/open-cabrita3b)
| Metric | Value |
|--------------------------|---------|
|Average |**33.04**|
|ENEM Challenge (No Images)| 17.98|
|BLUEX (No Images) | 21.14|
|OAB Exams | 22.69|
|Assin2 RTE | 43.01|
|Assin2 STS | 8.92|
|FaQuAD NLI | 43.97|
|HateBR Binary | 50.46|
|PT Hate Speech Binary | 41.19|
|tweetSentBR | 47.96|
|