CabraLlama3-70b / README.md
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---
language:
- pt
license: llama3
library_name: transformers
tags:
- portuguese
- llama
- cabra
- llama-3
datasets:
- botbot-ai/Cabra3k
model-index:
- name: CabraLlama3-70b
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: 82.02
name: accuracy
source:
url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=botbot-ai/CabraLlama3-70b
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: 70.1
name: accuracy
source:
url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=botbot-ai/CabraLlama3-70b
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: 68.52
name: accuracy
source:
url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=botbot-ai/CabraLlama3-70b
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: 93.21
name: f1-macro
source:
url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=botbot-ai/CabraLlama3-70b
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: 83.32
name: pearson
source:
url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=botbot-ai/CabraLlama3-70b
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: 80.6
name: f1-macro
source:
url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=botbot-ai/CabraLlama3-70b
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: 81.62
name: f1-macro
source:
url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=botbot-ai/CabraLlama3-70b
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: 72.72
name: f1-macro
source:
url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=botbot-ai/CabraLlama3-70b
name: Open Portuguese LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: tweetSentBR
type: eduagarcia/tweetsentbr_fewshot
split: test
args:
num_few_shot: 25
metrics:
- type: f1_macro
value: 73.85
name: f1-macro
source:
url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=botbot-ai/CabraLlama3-70b
name: Open Portuguese LLM Leaderboard
---
# Cabra Llama-3 70B
O Cabra Llama-3 70B é uma versão aprimorada do Meta Llama 3 70B Instruct, refinado com o uso do dataset Cabra 30k. Este modelo foi especialmente otimizado para compreender e responder em português (pt-br).
**Conheça os nossos outros [modelos e datasets](https://huggingface.co/collections/botbot-ai/models-6604c2069ceef04f834ba99b), e o [Cabra Llama 3 8b](https://huggingface.co/botbot-ai/CabraLlama3-8b).**
## Detalhes do modelo base
### Modelo: Meta-Llama-3-70B-Instruct
A Meta desenvolveu e lançou a família de modelos Llama 3, uma coleção de modelos de texto generativos pré-treinados e ajustados por instruções nos tamanhos de 8B e 70B. Os modelos Llama 3 ajustados por instruções são otimizados para casos de uso em diálogos e superam muitos dos modelos de chat de código aberto disponíveis em benchmarks comuns da indústria. Além disso, ao desenvolver esses modelos, tomamos grande cuidado para otimizar a utilidade e a segurança.
Arquitetura do Modelo: Llama 3 é um modelo de linguagem auto-regressivo que usa uma arquitetura de transformador otimizada. As versões ajustadas utilizam o aprimoramento supervisionado (SFT) e aprendizado por reforço com feedback humano (RLHF) para se alinhar às preferências humanas quanto à utilidade e segurança.
### Dataset: Cabra 30k
Dataset interno para fine-tuning. Vamos lançar em breve.
### Quantização / GGUF
Colocamos diversas versões (GGUF) quantanizadas no branch "quantanization".
# Open Portuguese LLM Leaderboard Evaluation Results
Detailed results can be found [here](https://huggingface.co/datasets/eduagarcia-temp/llm_pt_leaderboard_raw_results/tree/main/botbot-ai/CabraLlama3-70b) and on the [🚀 Open Portuguese LLM Leaderboard](https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard)
| Metric | Value |
|--------------------------|---------|
|Average |**78.44**|
|ENEM Challenge (No Images)| 82.02|
|BLUEX (No Images) | 70.10|
|OAB Exams | 68.52|
|Assin2 RTE | 93.21|
|Assin2 STS | 83.32|
|FaQuAD NLI | 80.60|
|HateBR Binary | 81.62|
|PT Hate Speech Binary | 72.72|
|tweetSentBR | 73.85|