leaderboard-pt-pr-bot
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Adding the Open Portuguese LLM Leaderboard Evaluation Results
Browse filesThis is an automated PR created with https://huggingface.co/spaces/eduagarcia-temp/portuguese-leaderboard-results-to-modelcard
The purpose of this PR is to add evaluation results from the Open Portuguese LLM Leaderboard to your model card.
If you encounter any issues, please report them to https://huggingface.co/spaces/eduagarcia-temp/portuguese-leaderboard-results-to-modelcard/discussions
README.md
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---
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library_name: peft
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tags:
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- Gemma
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- Portuguese
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- Bode
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- Alpaca
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license: mit
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language:
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-
- pt
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metrics:
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- accuracy
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- precision
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- f1
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- recall
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---
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# GemBode-2b-it
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@@ -110,4 +231,20 @@ Se você deseja utilizar o GemBode-2b-it em sua pesquisa, cite-o da seguinte man
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doi = { 10.57967/hf/1879 },
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publisher = { Hugging Face }
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}
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-
```
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---
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language:
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- pt
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license: mit
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library_name: peft
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tags:
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- Gemma
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- Portuguese
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- Bode
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- Alpaca
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metrics:
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- accuracy
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- precision
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- f1
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- recall
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model-index:
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- name: GemBode-2b-it
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results:
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: ENEM Challenge (No Images)
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type: eduagarcia/enem_challenge
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split: train
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args:
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num_few_shot: 3
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metrics:
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- type: acc
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value: 21.62
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name: accuracy
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source:
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url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=recogna-nlp/GemBode-2b-it
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name: Open Portuguese LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: BLUEX (No Images)
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type: eduagarcia-temp/BLUEX_without_images
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split: train
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args:
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num_few_shot: 3
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metrics:
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- type: acc
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value: 25.45
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name: accuracy
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source:
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url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=recogna-nlp/GemBode-2b-it
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name: Open Portuguese LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: OAB Exams
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type: eduagarcia/oab_exams
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split: train
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args:
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num_few_shot: 3
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metrics:
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- type: acc
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value: 27.33
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name: accuracy
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source:
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url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=recogna-nlp/GemBode-2b-it
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name: Open Portuguese LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: Assin2 RTE
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type: assin2
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split: test
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args:
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num_few_shot: 15
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metrics:
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- type: f1_macro
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value: 53.1
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name: f1-macro
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- type: pearson
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value: 15.57
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name: pearson
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source:
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url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=recogna-nlp/GemBode-2b-it
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name: Open Portuguese LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: FaQuAD NLI
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type: ruanchaves/faquad-nli
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split: test
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args:
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num_few_shot: 15
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metrics:
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- type: f1_macro
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value: 53.05
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name: f1-macro
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source:
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url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=recogna-nlp/GemBode-2b-it
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name: Open Portuguese LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: HateBR Binary
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type: eduagarcia/portuguese_benchmark
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split: test
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args:
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num_few_shot: 25
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metrics:
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- type: f1_macro
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value: 66.89
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name: f1-macro
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- type: f1_macro
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value: 24.22
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name: f1-macro
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source:
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url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=recogna-nlp/GemBode-2b-it
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name: Open Portuguese LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: tweetSentBR
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type: eduagarcia-temp/tweetsentbr
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split: test
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args:
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num_few_shot: 25
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metrics:
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- type: f1_macro
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value: 37.47
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name: f1-macro
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source:
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url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=recogna-nlp/GemBode-2b-it
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name: Open Portuguese LLM Leaderboard
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---
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# GemBode-2b-it
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doi = { 10.57967/hf/1879 },
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publisher = { Hugging Face }
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}
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```
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# [Open Portuguese LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard)
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Detailed results can be found [here](https://huggingface.co/datasets/eduagarcia-temp/llm_pt_leaderboard_raw_results/tree/main/recogna-nlp/GemBode-2b-it)
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| Metric | Value |
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|--------------------------|---------|
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|Average |**36.08**|
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|ENEM Challenge (No Images)| 21.62|
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|BLUEX (No Images) | 25.45|
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|OAB Exams | 27.33|
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|Assin2 RTE | 53.10|
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|Assin2 STS | 15.57|
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|FaQuAD NLI | 53.05|
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|HateBR Binary | 66.89|
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|PT Hate Speech Binary | 24.22|
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|tweetSentBR | 37.47|
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