metadata
license: mit
model-index:
- name: phi-bode-2-ultraalpaca
results:
- 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: 38.35
name: accuracy
source:
url: >-
https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=recogna-nlp/phi-bode-2-ultraalpaca
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: 25.17
name: accuracy
source:
url: >-
https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=recogna-nlp/phi-bode-2-ultraalpaca
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: 29.61
name: accuracy
source:
url: >-
https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=recogna-nlp/phi-bode-2-ultraalpaca
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: 45.39
name: f1-macro
source:
url: >-
https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=recogna-nlp/phi-bode-2-ultraalpaca
name: Open Portuguese LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: Assin2 STS
type: eduagarcia/portuguese_benchmark
split: test
args:
num_few_shot: 15
metrics:
- type: pearson
value: 24.43
name: pearson
source:
url: >-
https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=recogna-nlp/phi-bode-2-ultraalpaca
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=recogna-nlp/phi-bode-2-ultraalpaca
name: Open Portuguese LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: HateBR Binary
type: ruanchaves/hatebr
split: test
args:
num_few_shot: 25
metrics:
- type: f1_macro
value: 54.15
name: f1-macro
source:
url: >-
https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=recogna-nlp/phi-bode-2-ultraalpaca
name: Open Portuguese LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: PT Hate Speech Binary
type: hate_speech_portuguese
split: test
args:
num_few_shot: 25
metrics:
- type: f1_macro
value: 54.59
name: f1-macro
source:
url: >-
https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=recogna-nlp/phi-bode-2-ultraalpaca
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: 43.34
name: f1-macro
source:
url: >-
https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=recogna-nlp/phi-bode-2-ultraalpaca
name: Open Portuguese LLM Leaderboard
Phi-Bode
Phi-Bode é um modelo de linguagem ajustado para o idioma português, desenvolvido a partir do modelo base Phi-2B fornecido pela Microsoft. Este modelo foi refinado através do processo de fine-tuning utilizando o dataset UltraAlpaca. O principal objetivo deste modelo é ser viável para pessoas que não possuem recursos computacionais disponíveis para o uso de LLMs (Large Language Models). Ressalta-se que este é um trabalho em andamento e o modelo ainda apresenta problemas na geração de texto em português.
Características Principais
- Modelo Base: Phi-2B, criado pela Microsoft, com 2.7 bilhões de parâmetros.
- Dataset para Fine-tuning: UltraAlpaca
- Treinamento: O treinamento foi realizado a partir do fine-tuning completo do phi-2.
Open Portuguese LLM Leaderboard Evaluation Results
Detailed results can be found here
Metric | Value |
---|---|
Average | 39.89 |
ENEM Challenge (No Images) | 38.35 |
BLUEX (No Images) | 25.17 |
OAB Exams | 29.61 |
Assin2 RTE | 45.39 |
Assin2 STS | 24.43 |
FaQuAD NLI | 43.97 |
HateBR Binary | 54.15 |
PT Hate Speech Binary | 54.59 |
tweetSentBR | 43.34 |