botbot-ai/CabraMistral7b

Cabra Mistral 7b v2

Esse modelo é um finetune do Mistral 7b Instruct 0.2 com o dataset interno Cabra 10k. Esse modelo é optimizado para português. Ele apresenta melhoria em varios benchmarks brasileiros em comparação com o modelo base.

Conheça os nossos outros modelos: Cabra.

Detalhes do Modelo

Modelo: Mistral 7b Instruct 0.2

Mistral-7B-v0.1 é um modelo de transformador, com as seguintes escolhas arquitetônicas:

• Grouped-Query Attention
• Sliding-Window Attention
• Byte-fallback BPE tokenizer

dataset: Cabra 10k

Dataset interno para finetuning. Vamos lançar em breve.

Quantização / GGUF

Colocamos diversas versões (GGUF) quantanizadas no branch "quantanization".

Exemplo

<s> [INST] who is Elon Musk? [/INST]Elon Musk é um empreendedor, inventor e capitalista americano. Ele é o fundador, CEO e CTO da SpaceX, CEO da Neuralink e fundador do The Boring Company. Musk também é o proprietário do Twitter.</s>

Paramentros de trainamento

- learning_rate: 1e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- total_eval_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.01
- num_epochs: 3

Framework

• Transformers 4.39.0.dev0
• Pytorch 2.1.2+cu118
• Datasets 2.14.6
• Tokenizers 0.15.2

Uso

O modelo é destinado, por agora, a fins de pesquisa. As áreas e tarefas de pesquisa possíveis incluem:

• Pesquisa sobre modelos gerativos.
• Investigação e compreensão das limitações e viéses de modelos gerativos.

Proibido para uso comercial. Somente Pesquisa.

Evals

Tasks	Version	Filter	n-shot	Metric	Value	Stderr
assin2_rte	1.1	all	15	f1_macro	0.9013	± 0.0043
		all	15	acc	0.9016	± 0.0043
assin2_sts	1.1	all	15	pearson	0.7151	± 0.0074
		all	15	mse	0.6803	± N/A
bluex	1.1	all	3	acc	0.4798	± 0.0107
		exam_id__USP_2019	3	acc	0.375	± 0.044
		exam_id__USP_2021	3	acc	0.3462	± 0.0382
		exam_id__USP_2020	3	acc	0.4107	± 0.0379
		exam_id__UNICAMP_2018	3	acc	0.4815	± 0.0392
		exam_id__UNICAMP_2020	3	acc	0.4727	± 0.0389
		exam_id__UNICAMP_2021_1	3	acc	0.413	± 0.0418
		exam_id__UNICAMP_2019	3	acc	0.42	± 0.0404
		exam_id__UNICAMP_2022	3	acc	0.5897	± 0.0456
		exam_id__USP_2022	3	acc	0.449	± 0.041
		exam_id__USP_2024	3	acc	0.6341	± 0.0434
		exam_id__UNICAMP_2024	3	acc	0.6	± 0.0422
		exam_id__USP_2023	3	acc	0.5455	± 0.0433
		exam_id__UNICAMP_2023	3	acc	0.5349	± 0.044
		exam_id__USP_2018	3	acc	0.4815	± 0.0393
		exam_id__UNICAMP_2021_2	3	acc	0.5098	± 0.0403
enem	1.1	all	3	acc	0.5843	± 0.0075
		exam_id__2010	3	acc	0.5726	± 0.0264
		exam_id__2009	3	acc	0.6	± 0.0264
		exam_id__2014	3	acc	0.633	± 0.0268
		exam_id__2022	3	acc	0.6165	± 0.0243
		exam_id__2012	3	acc	0.569	± 0.0265
		exam_id__2013	3	acc	0.5833	± 0.0274
		exam_id__2016_2	3	acc	0.5203	± 0.026
		exam_id__2011	3	acc	0.6325	± 0.0257
		exam_id__2023	3	acc	0.5778	± 0.0246
		exam_id__2016	3	acc	0.595	± 0.0258
		exam_id__2017	3	acc	0.5517	± 0.0267
		exam_id__2015	3	acc	0.563	± 0.0261
faquad_nli	1.1	all	15	f1_macro	0.6424	± 0.0138
		all	15	acc	0.6769	± 0.013
hatebr_offensive_binary	1	all	25	f1_macro	0.8361	± 0.007
		all	25	acc	0.8371	± 0.007
oab_exams	1.5	all	3	acc	0.3841	± 0.006
		exam_id__2011-03	3	acc	0.3636	± 0.0279
		exam_id__2014-14	3	acc	0.475	± 0.0323
		exam_id__2016-21	3	acc	0.4125	± 0.0318
		exam_id__2012-06a	3	acc	0.3875	± 0.0313
		exam_id__2014-13	3	acc	0.325	± 0.0303
		exam_id__2015-16	3	acc	0.425	± 0.032
		exam_id__2010-02	3	acc	0.4	± 0.0283
		exam_id__2012-08	3	acc	0.3875	± 0.0314
		exam_id__2011-05	3	acc	0.375	± 0.0312
		exam_id__2017-22	3	acc	0.4	± 0.0316
		exam_id__2018-25	3	acc	0.4125	± 0.0318
		exam_id__2012-09	3	acc	0.3636	± 0.0317
		exam_id__2017-24	3	acc	0.3375	± 0.0304
		exam_id__2016-20a	3	acc	0.3125	± 0.0299
		exam_id__2012-06	3	acc	0.425	± 0.0318
		exam_id__2013-12	3	acc	0.4375	± 0.0321
		exam_id__2016-20	3	acc	0.45	± 0.0322
		exam_id__2013-11	3	acc	0.4	± 0.0316
		exam_id__2015-17	3	acc	0.4231	± 0.0323
		exam_id__2015-18	3	acc	0.4	± 0.0316
		exam_id__2017-23	3	acc	0.35	± 0.0308
		exam_id__2010-01	3	acc	0.2471	± 0.0271
		exam_id__2011-04	3	acc	0.375	± 0.0313
		exam_id__2016-19	3	acc	0.4103	± 0.0321
		exam_id__2013-10	3	acc	0.3375	± 0.0305
		exam_id__2012-07	3	acc	0.3625	± 0.031
		exam_id__2014-15	3	acc	0.3846	± 0.0318
portuguese_hate_speech_binary	1	all	25	f1_macro	0.6187	± 0.0119
		all	25	acc	0.6322	± 0.0117

Open Portuguese LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric	Value
Average	65.1
ENEM Challenge (No Images)	60.81
BLUEX (No Images)	46.87
OAB Exams	38.59
Assin2 RTE	90.27
Assin2 STS	72.25
FaQuAD NLI	64.35
HateBR Binary	83.15
PT Hate Speech Binary	64.82
tweetSentBR	64.80