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README.md
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@@ -59,4 +59,39 @@ Below, you can see the F1 score on several text classification datasets. All tes
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| [Bart-large-mnli (407 M)](https://huggingface.co/facebook/bart-large-mnli) | 0.89 | 0.6887 | 0.3765 |
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| [Deberta-base-v3 (184 M)](https://huggingface.co/cross-encoder/nli-deberta-v3-base) | 0.85 | 0.6455 | 0.5095 |
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| [Comprehendo (184M)](https://huggingface.co/knowledgator/comprehend_it-base) | 0.90 | 0.7982 | 0.5660 |
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| SetFit [BAAI/bge-small-en-v1.5 (33.4M)](https://huggingface.co/BAAI/bge-small-en-v1.5) | 0.86 | 0.5636 | 0.5754 |
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| [Bart-large-mnli (407 M)](https://huggingface.co/facebook/bart-large-mnli) | 0.89 | 0.6887 | 0.3765 |
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| [Deberta-base-v3 (184 M)](https://huggingface.co/cross-encoder/nli-deberta-v3-base) | 0.85 | 0.6455 | 0.5095 |
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| [Comprehendo (184M)](https://huggingface.co/knowledgator/comprehend_it-base) | 0.90 | 0.7982 | 0.5660 |
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| SetFit [BAAI/bge-small-en-v1.5 (33.4M)](https://huggingface.co/BAAI/bge-small-en-v1.5) | 0.86 | 0.5636 | 0.5754 |
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Below you can find a comparison with other GLiClass models:
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| Dataset | gliclass-small-v1.0-lw | gliclass-base-v1.0-lw | gliclass-large-v1.0-lw | gliclass-small-v1.0 | gliclass-base-v1.0 | gliclass-large-v1.0 |
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|----------------------|-----------------------|-----------------------|-----------------------|---------------------|---------------------|---------------------|
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| CR | 0.8886 | 0.9097 | 0.9226 | 0.8824 | 0.8942 | 0.9219 |
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| sst2 | 0.8392 | 0.8987 | 0.9247 | 0.8518 | 0.8979 | 0.9269 |
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| sst5 | 0.2865 | 0.3779 | 0.2891 | 0.2424 | 0.2789 | 0.3900 |
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| 20_news_groups | 0.4572 | 0.3953 | 0.4083 | 0.3366 | 0.3576 | 0.3863 |
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| spam | 0.5118 | 0.5126 | 0.3642 | 0.4089 | 0.4938 | 0.3661 |
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| rotten_tomatoes | 0.8015 | 0.8429 | 0.8807 | 0.7987 | 0.8508 | 0.8808 |
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| massive | 0.3180 | 0.4635 | 0.5606 | 0.2546 | 0.1893 | 0.4376 |
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| banking | 0.1768 | 0.4396 | 0.3317 | 0.1374 | 0.2077 | 0.2847 |
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| yahoo_topics | 0.4686 | 0.4784 | 0.4760 | 0.4477 | 0.4516 | 0.4921 |
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| financial_phrasebank | 0.8665 | 0.8880 | 0.9044 | 0.8901 | 0.8955 | 0.8735 |
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| imdb | 0.9048 | 0.9351 | 0.9429 | 0.8982 | 0.9238 | 0.9333 |
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| ag_news | 0.7252 | 0.6985 | 0.7559 | 0.7242 | 0.6848 | 0.7503 |
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| dair_emotion | 0.4012 | 0.3516 | 0.3951 | 0.3450 | 0.2357 | 0.4013 |
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| capsotu | 0.3794 | 0.4643 | 0.4749 | 0.3432 | 0.4375 | 0.4644 |
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|Average:|0.5732|0.6183|0.6165|0.5401|0.5571|0.6078|
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Here you can see how the performance of the model grows providing more examples:
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| Model | Num Examples | sst5 | spam | massive | banking | ag news | dair emotion | capsotu | Average |
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|-----------------------------|--------------|--------|---------|---------|---------|---------|--------------|---------|-------------|
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| gliclass-small-v1.0-lw | 0 | 0.2865 | 0.5118 | 0.318 | 0.1768 | 0.7252 | 0.4012 | 0.3794 | 0.3998428571|
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| gliclass-base-v1.0-lw | 0 | 0.3779 | 0.5126 | 0.4635 | 0.4396 | 0.6985 | 0.3516 | 0.4643 | 0.4725714286|
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| gliclass-large-v1.0-lw | 0 | 0.2891 | 0.3642 | 0.5606 | 0.3317 | 0.7559 | 0.3951 | 0.4749 | 0.4530714286|
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| gliclass-small-v1.0 | 0 | 0.2424 | 0.4089 | 0.2546 | 0.1374 | 0.7242 | 0.345 | 0.3432 | 0.3508142857|
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| gliclass-base-v1.0 | 0 | 0.2789 | 0.4938 | 0.1893 | 0.2077 | 0.6848 | 0.2357 | 0.4375 | 0.3611 |
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| gliclass-large-v1.0 | 0 | 0.39 | 0.3661 | 0.4376 | 0.2847 | 0.7503 | 0.4013 | 0.4644 | 0.4420571429|
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| gliclass-small-v1.0-lw | 8 | 0.2709 | 0.84026 | 0.62 | 0.6883 | 0.7786 | 0.449 | 0.4918 | 0.5912657143|
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| gliclass-base-v1.0-lw | 8 | 0.4275 | 0.8836 | 0.729 | 0.7667 | 0.7968 | 0.3866 | 0.4858 | 0.6394285714|
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| gliclass-large-v1.0-lw | 8 | 0.3345 | 0.8997 | 0.7658 | 0.848 | 0.84843 | 0.5219 | 0.508 | 0.67519 |
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| gliclass-small-v1.0 | 8 | 0.3042 | 0.5683 | 0.6332 | 0.7072 | 0.759 | 0.4509 | 0.4434 | 0.5523142857|
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| gliclass-base-v1.0 | 8 | 0.3387 | 0.7361 | 0.7059 | 0.7456 | 0.7896 | 0.4323 | 0.4802 | 0.6040571429|
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| gliclass-large-v1.0 | 8 | 0.4365 | 0.9018 | 0.77 | 0.8533 | 0.8509 | 0.5061 | 0.4935 | 0.6874428571|
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