--- license: other license_name: yi-34b license_link: https://huggingface.co/01-ai/Yi-34B/blob/main/LICENSE model-index: - name: Tess-M-v1.3 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: 72.36 name: accuracy source: url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=migtissera/Tess-M-v1.3 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: 64.81 name: accuracy source: url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=migtissera/Tess-M-v1.3 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: 55.58 name: accuracy source: url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=migtissera/Tess-M-v1.3 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: 91.46 name: f1-macro source: url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=migtissera/Tess-M-v1.3 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: 78.33 name: pearson source: url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=migtissera/Tess-M-v1.3 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: 80.55 name: f1-macro source: url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=migtissera/Tess-M-v1.3 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: 73.97 name: f1-macro source: url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=migtissera/Tess-M-v1.3 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: 66.63 name: f1-macro source: url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=migtissera/Tess-M-v1.3 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: 73.99 name: f1-macro source: url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=migtissera/Tess-M-v1.3 name: Open Portuguese LLM Leaderboard --- # Note: This version is the stable release. The issues that were present in versions 1.0, 1.1 and 1.2 all have been rectified. Thank you for your patience while R&D was conducted. Enjoy! This model have been tested on very long context length. Model produced slight repetition, but it was very minor. I recommend testing the model to your usecase and limiting the context length. Here's my conversation: https://migel.substack.com/p/testing-tess-m-v13 As can be seen, "USER:" and "SYSTEM: Answer the question thoughtfully and intelligently. Always answer without hesitation." was presented by the model in the latter part of the conversation. # Learnings: Here's my learnings going from Tess-v1.0 to Tess-v1.3: https://migel.substack.com/p/learnings-from-training-tess # Tess ![Tess](https://huggingface.co/migtissera/Tess-M-v1.0/resolve/main/Tess.png) Tess, short for Tesoro (Treasure in Italian), is a general purpose Large Language Model series. Tess-M-v1.3 was trained on the Yi-34B-200K base. # Prompt Format: ``` SYSTEM: USER: ASSISTANT: ``` # 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/migtissera/Tess-M-v1.3) and on the [🚀 Open Portuguese LLM Leaderboard](https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard) | Metric | Value | |--------------------------|---------| |Average |**73.08**| |ENEM Challenge (No Images)| 72.36| |BLUEX (No Images) | 64.81| |OAB Exams | 55.58| |Assin2 RTE | 91.46| |Assin2 STS | 78.33| |FaQuAD NLI | 80.55| |HateBR Binary | 73.97| |PT Hate Speech Binary | 66.63| |tweetSentBR | 73.99|