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license: apache-2.0 |
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extra_gated_fields: |
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Name: text |
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Country: country |
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Institution: text |
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Institution Email: text |
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Please specify your academic use case: text |
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extra_gated_prompt: Our models are intended for academic use only. If you are not |
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affiliated with an academic institution, please provide a rationale for using our |
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models. Please allow us a few business days to manually review subscriptions. |
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--- |
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[README UNDER CONSTRUCTION] |
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emBert is a Hungarian text classification model, aimed at classifying 7 possible emotions and a neutral state. The model uses [huBERT](https://huggingface.co/SZTAKI-HLT/hubert-base-cc) tokenizer, and was fine-tuned on a [huBERT](https://huggingface.co/SZTAKI-HLT/hubert-base-cc) base model with a proprietary database of Hungarian online news site sentences. The sentences for the fine-tuning set were classified manually by experts in a double-blind manner. Inconsistencies were dealt with manually. |
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The results of the fine-tuning validation were: |
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| emotion | precision | recall | f1-score | |
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| ------- | --------- | ------ | -------- | |
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|0 - Anger| 0.70 | 0.74 | 0.72 | |
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|1 - Disgust| 0.72 | 0.73 | 0.73| |
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|2 - Fear|0.61 | 0.47 | 0.53| |
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|3 - Happiness|0.38 | 0.37 | 0.38| |
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|4 - Neutral|0.65 | 0.62 | 0.63| |
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|5 - Sad|0.74 | 0.72 | 0.73| |
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|6 - Successful|0.79 |0.81 | 0.80| |
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|7 - Trustful|0.76 |0.78 |0.77| |
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|weighted avg|0.73 | 0.74 | 0.73| |
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Accuracy reached 74%. |
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The emotions are based on [Plutchik 1980](https://doi.org/10.1016/B978-0-12-558701-3.50007-7), with anticipation substituted with neutral. |
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Proper use of the model: |
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``` |
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from transformers import AutoTokenizer, AutoModelForSequenceClassification |
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tokenizer = AutoTokenizer.from_pretrained("SZTAKI-HLT/hubert-base-cc") |
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model = AutoModelForSequenceClassification.from_pretrained("poltextlab/emBERT") |
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``` |
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The model was created by György Márk Kis, Orsolya Ring, Miklós Sebők of the Center for Social Sciences. |
