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--- |
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language: |
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- pt |
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- en |
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license: cc |
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tags: |
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- text-generation-inference |
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- transformers |
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- mistral |
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- gguf |
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- brazil |
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- brasil |
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- portuguese |
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base_model: mistralai/Mistral-7B-Instruct-v0.2 |
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pipeline_tag: text-generation |
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metrics: |
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- name: assin2_rte f1_macro |
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type: assin2_rte |
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value: 90.13 |
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- name: assin2_rte acc |
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type: assin2_rte |
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value: 90.16 |
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- name: assin2_sts pearson |
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type: assin2_sts |
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value: 71.51 |
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- name: assin2_sts mse |
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type: assin2_sts |
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value: 68.03 |
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- name: bluex acc |
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type: bluex |
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value: 47.98 |
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- name: enem acc |
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type: enem |
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value: 58.43 |
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- name: faquad_nli f1_macro |
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type: faquad_nli |
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value: 64.24 |
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- name: faquad_nli acc |
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type: faquad_nli |
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value: 67.69 |
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- name: hatebr_offensive_binary f1_macro |
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type: hatebr_offensive_binary |
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value: 83.61 |
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- name: hatebr_offensive_binary acc |
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type: hatebr_offensive_binary |
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value: 83.71 |
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- name: oab_exams acc |
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type: oab_exams |
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value: 38.41 |
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- name: portuguese_hate_speech_binary f1_macro |
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type: portuguese_hate_speech_binary |
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value: 61.87 |
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- name: portuguese_hate_speech_binary acc |
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type: portuguese_hate_speech_binary |
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value: 63.22 |
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--- |
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# Cabra Mistral 7b v2 |
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<img src="https://uploads-ssl.webflow.com/65f77c0240ae1c68f8192771/660b1a4d574293d8a1ce48ca_cabra1.png" width="400" height="400"> |
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Esse modelo é um finetune do [Mistral 7b Instruct 0.2](https://huggingface.co/mistralai/mistral-7b-instruct-v0.2) 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. |
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**Exprimente o nosso demo aqui: [CabraChat](https://huggingface.co/spaces/nicolasdec/CabraChat).** |
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**Conheça os nossos outros modelos: [Cabra](https://huggingface.co/collections/botbot-ai/models-6604c2069ceef04f834ba99b).** |
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## Detalhes do Modelo |
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### Modelo: Mistral 7b Instruct 0.2 |
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Mistral-7B-v0.1 é um modelo de transformador, com as seguintes escolhas arquitetônicas: |
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- Grouped-Query Attention |
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- Sliding-Window Attention |
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- Byte-fallback BPE tokenizer |
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### dataset: Cabra 10k |
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Dataset interno para finetuning. Vamos lançar em breve. |
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### Quantização / GGUF |
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Colocamos diversas versões (GGUF) quantanizadas no branch "quantanization". |
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### Exemplo |
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``` |
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<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> |
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``` |
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### Paramentros de trainamento |
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``` |
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- learning_rate: 1e-05 |
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- train_batch_size: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 2 |
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- gradient_accumulation_steps: 8 |
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- total_train_batch_size: 64 |
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- total_eval_batch_size: 8 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_ratio: 0.01 |
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- num_epochs: 3 |
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``` |
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### Framework |
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- Transformers 4.39.0.dev0 |
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- Pytorch 2.1.2+cu118 |
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- Datasets 2.14.6 |
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- Tokenizers 0.15.2 |
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## Uso |
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O modelo é destinado, por agora, a fins de pesquisa. As áreas e tarefas de pesquisa possíveis incluem: |
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- Pesquisa sobre modelos gerativos. |
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- Investigação e compreensão das limitações e viéses de modelos gerativos. |
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**Proibido para uso comercial. Somente Pesquisa.** |
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### Evals |
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| Tasks | Version | Filter | n-shot | Metric | Value | Stderr | |
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|-----------------------------|---------|----------------------|--------|----------|--------|---------| |
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| assin2_rte | 1.1 | all | 15 | f1_macro | 0.9013 | ± 0.0043 | |
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| | | all | 15 | acc | 0.9016 | ± 0.0043 | |
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| assin2_sts | 1.1 | all | 15 | pearson | 0.7151 | ± 0.0074 | |
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| | | all | 15 | mse | 0.6803 | ± N/A | |
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| bluex | 1.1 | all | 3 | acc | 0.4798 | ± 0.0107 | |
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| | | exam_id__USP_2019 | 3 | acc | 0.375 | ± 0.044 | |
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| | | exam_id__USP_2021 | 3 | acc | 0.3462 | ± 0.0382 | |
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| | | exam_id__USP_2020 | 3 | acc | 0.4107 | ± 0.0379 | |
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| | | exam_id__UNICAMP_2018| 3 | acc | 0.4815 | ± 0.0392 | |
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| | | exam_id__UNICAMP_2020| 3 | acc | 0.4727 | ± 0.0389 | |
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| | | exam_id__UNICAMP_2021_1| 3 | acc | 0.413 | ± 0.0418 | |
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| | | exam_id__UNICAMP_2019| 3 | acc | 0.42 | ± 0.0404 | |
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| | | exam_id__UNICAMP_2022| 3 | acc | 0.5897 | ± 0.0456 | |
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| | | exam_id__USP_2022 | 3 | acc | 0.449 | ± 0.041 | |
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| | | exam_id__USP_2024 | 3 | acc | 0.6341 | ± 0.0434 | |
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| | | exam_id__UNICAMP_2024| 3 | acc | 0.6 | ± 0.0422 | |
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| | | exam_id__USP_2023 | 3 | acc | 0.5455 | ± 0.0433 | |
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| | | exam_id__UNICAMP_2023| 3 | acc | 0.5349 | ± 0.044 | |
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| | | exam_id__USP_2018 | 3 | acc | 0.4815 | ± 0.0393 | |
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| | | exam_id__UNICAMP_2021_2| 3 | acc | 0.5098 | ± 0.0403 | |
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| enem | 1.1 | all | 3 | acc | 0.5843 | ± 0.0075 | |
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| | | exam_id__2010 | 3 | acc | 0.5726 | ± 0.0264 | |
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| | | exam_id__2009 | 3 | acc | 0.6 | ± 0.0264 | |
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| | | exam_id__2014 | 3 | acc | 0.633 | ± 0.0268 | |
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| | | exam_id__2022 | 3 | acc | 0.6165 | ± 0.0243 | |
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| | | exam_id__2012 | 3 | acc | 0.569 | ± 0.0265 | |
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| | | exam_id__2013 | 3 | acc | 0.5833 | ± 0.0274 | |
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| | | exam_id__2016_2 | 3 | acc | 0.5203 | ± 0.026 | |
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| | | exam_id__2011 | 3 | acc | 0.6325 | ± 0.0257 | |
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| | | exam_id__2023 | 3 | acc | 0.5778 | ± 0.0246 | |
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| | | exam_id__2016 | 3 | acc | 0.595 | ± 0.0258 | |
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| | | exam_id__2017 | 3 | acc | 0.5517 | ± 0.0267 | |
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| | | exam_id__2015 | 3 | acc | 0.563 | ± 0.0261 | |
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| faquad_nli | 1.1 | all | 15 | f1_macro | 0.6424 | ± 0.0138 | |
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| | | all | 15 | acc | 0.6769 | ± 0.013 | |
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| hatebr_offensive_binary | 1 | all | 25 | f1_macro | 0.8361 | ± 0.007 | |
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| | | all | 25 | acc | 0.8371 | ± 0.007 | |
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| oab_exams | 1.5 | all | 3 | acc | 0.3841 | ± 0.006 | |
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| | | exam_id__2011-03 | 3 | acc | 0.3636 | ± 0.0279 | |
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| | | exam_id__2014-14 | 3 | acc | 0.475 | ± 0.0323 | |
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| | | exam_id__2016-21 | 3 | acc | 0.4125 | ± 0.0318 | |
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| | | exam_id__2012-06a | 3 | acc | 0.3875 | ± 0.0313 | |
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| | | exam_id__2014-13 | 3 | acc | 0.325 | ± 0.0303 | |
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| | | exam_id__2015-16 | 3 | acc | 0.425 | ± 0.032 | |
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| | | exam_id__2010-02 | 3 | acc | 0.4 | ± 0.0283 | |
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| | | exam_id__2012-08 | 3 | acc | 0.3875 | ± 0.0314 | |
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| | | exam_id__2011-05 | 3 | acc | 0.375 | ± 0.0312 | |
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| | | exam_id__2017-22 | 3 | acc | 0.4 | ± 0.0316 | |
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| | | exam_id__2018-25 | 3 | acc | 0.4125 | ± 0.0318 | |
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| | | exam_id__2012-09 | 3 | acc | 0.3636 | ± 0.0317 | |
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| | | exam_id__2017-24 | 3 | acc | 0.3375 | ± 0.0304 | |
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| | | exam_id__2016-20a | 3 | acc | 0.3125 | ± 0.0299 | |
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| | | exam_id__2012-06 | 3 | acc | 0.425 | ± 0.0318 | |
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| | | exam_id__2013-12 | 3 | acc | 0.4375 | ± 0.0321 | |
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| | | exam_id__2016-20 | 3 | acc | 0.45 | ± 0.0322 | |
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| | | exam_id__2013-11 | 3 | acc | 0.4 | ± 0.0316 | |
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| | | exam_id__2015-17 | 3 | acc | 0.4231 | ± 0.0323 | |
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| | | exam_id__2015-18 | 3 | acc | 0.4 | ± 0.0316 | |
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| | | exam_id__2017-23 | 3 | acc | 0.35 | ± 0.0308 | |
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| | | exam_id__2010-01 | 3 | acc | 0.2471 | ± 0.0271 | |
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| | | exam_id__2011-04 | 3 | acc | 0.375 | ± 0.0313 | |
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| | | exam_id__2016-19 | 3 | acc | 0.4103 | ± 0.0321 | |
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| | | exam_id__2013-10 | 3 | acc | 0.3375 | ± 0.0305 | |
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| | | exam_id__2012-07 | 3 | acc | 0.3625 | ± 0.031 | |
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| | | exam_id__2014-15 | 3 | acc | 0.3846 | ± 0.0318 | |
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| portuguese_hate_speech_binary | 1 | all | 25 | f1_macro | 0.6187 | ± 0.0119 | |
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| | | all | 25 | acc | 0.6322 | ± 0.0117 | |
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