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from dataclasses import dataclass |
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from enum import Enum |
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@dataclass |
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class Task: |
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benchmark: str |
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metric: str |
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col_name: str |
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class Tasks(Enum): |
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task0 = Task("FPB", "F1", "FPB-F1") |
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task1 = Task("FPB", "Acc", "FPB-Acc") |
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task2 = Task("FiQA-SA", "F1", "FiQA-SA-F1") |
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task3 = Task("TSA", "RMSE", "TSA-RMSE") |
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task4 = Task("Headlines", "AvgF1", "Headlines-AvgF1") |
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task5 = Task("FOMC", "F1", "FOMC-F1") |
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task6 = Task("FOMC", "Acc", "FOMC-Acc") |
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task7 = Task("FinArg-ACC", "MicroF1", "FinArg-ACC-MicroF1") |
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task8 = Task("FinArg-ARC", "MicroF1", "FinArg-ARC-MicroF1") |
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task9 = Task("MultiFin", "MicroF1", "Multifin-MicroF1") |
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task10 = Task("MA", "MicroF1", "MA-MicroF1") |
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task11 = Task("MLESG", "MicroF1", "MLESG-MicroF1") |
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task12 = Task("NER", "EntityF1", "NER-EntityF1") |
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task13 = Task("FINER-ORD", "EntityF1", "FINER-ORD-EntityF1") |
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task14 = Task("FinRED", "F1", "FinRED-F1") |
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task15 = Task("SC", "F1", "SC-F1") |
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task16 = Task("CD", "F1", "CD-F1") |
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task17 = Task("FinQA", "EmAcc", "FinQA-EmAcc") |
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task18 = Task("TATQA", "EmAcc", "TATQA-EmAcc") |
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task19 = Task("ConvFinQA", "EmAcc", "ConvFinQA-EmAcc") |
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task20 = Task("FNXL", "EntityF1", "FNXL-EntityF1") |
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task21 = Task("FSRL", "EntityF1", "FSRL-EntityF1") |
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task22 = Task("EDTSUM", "Rouge-1", "EDTSUM-Rouge-1") |
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task23 = Task("EDTSUM", "BertScore", "EDTSUM-BertScore") |
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task24 = Task("EDTSUM", "BartScore", "EDTSUM-BartScore") |
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task25 = Task("ECTSUM", "Rouge-1", "ECTSUM-Rouge-1") |
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task26 = Task("ECTSUM", "BertScore", "ECTSUM-BertScore") |
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task27 = Task("ECTSUM", "BartScore", "ECTSUM-BartScore") |
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task28 = Task("BigData22", "Acc", "BigData22-Acc") |
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task29 = Task("BigData22", "MCC", "BigData22-MCC") |
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task30 = Task("ACL18", "Acc", "ACL18-Acc") |
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task31 = Task("ACL18", "MCC", "ACL18-MCC") |
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task32 = Task("CIKM18", "Acc", "CIKM18-Acc") |
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task33 = Task("CIKM18", "MCC", "CIKM18-MCC") |
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task34 = Task("German", "F1", "German-F1") |
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task35 = Task("German", "MCC", "German-MCC") |
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task36 = Task("Australian", "F1", "Australian-F1") |
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task37 = Task("Australian", "MCC", "Australian-MCC") |
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task38 = Task("LendingClub", "F1", "LendingClub-F1") |
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task39 = Task("LendingClub", "MCC", "LendingClub-MCC") |
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task40 = Task("ccf", "F1", "ccf-F1") |
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task41 = Task("ccf", "MCC", "ccf-MCC") |
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task42 = Task("ccfraud", "F1", "ccfraud-F1") |
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task43 = Task("ccfraud", "MCC", "ccfraud-MCC") |
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task44 = Task("polish", "F1", "polish-F1") |
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task45 = Task("polish", "MCC", "polish-MCC") |
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task46 = Task("taiwan", "F1", "taiwan-F1") |
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task47 = Task("taiwan", "MCC", "taiwan-MCC") |
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task48 = Task("portoseguro", "F1", "portoseguro-F1") |
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task49 = Task("portoseguro", "MCC", "portoseguro-MCC") |
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task50 = Task("travelinsurance", "F1", "travelinsurance-F1") |
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task51 = Task("travelinsurance", "MCC", "travelinsurance-MCC") |
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NUM_FEWSHOT = 0 |
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TITLE = """<h1 align="center" id="space-title">Demo leaderboard</h1>""" |
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INTRODUCTION_TEXT = """ |
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Intro text |
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""" |
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LLM_BENCHMARKS_TEXT = f""" |
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## How it works |
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## Reproducibility |
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To reproduce our results, here is the commands you can run: |
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""" |
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EVALUATION_QUEUE_TEXT = """ |
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## Some good practices before submitting a model |
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### 1) Make sure you can load your model and tokenizer using AutoClasses: |
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```python |
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from transformers import AutoConfig, AutoModel, AutoTokenizer |
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config = AutoConfig.from_pretrained("your model name", revision=revision) |
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model = AutoModel.from_pretrained("your model name", revision=revision) |
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tokenizer = AutoTokenizer.from_pretrained("your model name", revision=revision) |
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``` |
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If this step fails, follow the error messages to debug your model before submitting it. It's likely your model has been improperly uploaded. |
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Note: make sure your model is public! |
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Note: if your model needs `use_remote_code=True`, we do not support this option yet but we are working on adding it, stay posted! |
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### 2) Convert your model weights to [safetensors](https://huggingface.co/docs/safetensors/index) |
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It's a new format for storing weights which is safer and faster to load and use. It will also allow us to add the number of parameters of your model to the `Extended Viewer`! |
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### 3) Make sure your model has an open license! |
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This is a leaderboard for Open LLMs, and we'd love for as many people as possible to know they can use your model 🤗 |
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### 4) Fill up your model card |
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When we add extra information about models to the leaderboard, it will be automatically taken from the model card |
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## In case of model failure |
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If your model is displayed in the `FAILED` category, its execution stopped. |
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Make sure you have followed the above steps first. |
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If everything is done, check you can launch the EleutherAIHarness on your model locally, using the above command without modifications (you can add `--limit` to limit the number of examples per task). |
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""" |
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CITATION_BUTTON_LABEL = "Copy the following snippet to cite these results" |
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CITATION_BUTTON_TEXT = r""" |
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""" |
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