| --- |
| language: |
| - hu |
| license: cc-by-4.0 |
| extra_gated_fields: |
| Country: country |
| Institution: text |
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| --- |
| |
| [README UNDER CONSTRUCTION] |
|
|
| 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. |
| The results of the fine-tuning validation were: |
|
|
| | emotion | precision | recall | f1-score | |
| | ------- | --------- | ------ | -------- | |
| |0 - Anger| 0.70 | 0.74 | 0.72 | |
| |1 - Disgust| 0.72 | 0.73 | 0.73| |
| |2 - Fear|0.61 | 0.47 | 0.53| |
| |3 - Happiness|0.38 | 0.37 | 0.38| |
| |4 - Neutral|0.65 | 0.62 | 0.63| |
| |5 - Sad|0.74 | 0.72 | 0.73| |
| |6 - Successful|0.79 |0.81 | 0.80| |
| |7 - Trustful|0.76 |0.78 |0.77| |
| |weighted avg|0.73 | 0.74 | 0.73| |
| Accuracy reached 74%. |
|
|
| The emotions are based on [Plutchik 1980](https://doi.org/10.1016/B978-0-12-558701-3.50007-7), with anticipation substituted with neutral. |
|
|
| Proper use of the model: |
|
|
| ``` |
| from transformers import AutoTokenizer, AutoModelForSequenceClassification |
| |
| tokenizer = AutoTokenizer.from_pretrained("SZTAKI-HLT/hubert-base-cc") |
| |
| model = AutoModelForSequenceClassification.from_pretrained("poltextlab/emBERT") |
| ``` |
|
|
| The model was created by György Márk Kis, Orsolya Ring, Miklós Sebők of the Center for Social Sciences. |
