SeyedAli/Persian-Text-Emotion
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How to use NLPclass/bert_classification_persian_emotion with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="NLPclass/bert_classification_persian_emotion") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("NLPclass/bert_classification_persian_emotion")
model = AutoModelForSequenceClassification.from_pretrained("NLPclass/bert_classification_persian_emotion")This model is a fine-tuned version of HooshvareLab/bert-base-parsbert-uncased on an unknown dataset. It achieves the following results on the evaluation set:
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The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.3557 | 1.0 | 348 | 1.1649 |
| 0.4685 | 2.0 | 696 | 0.4005 |
| 0.2652 | 3.0 | 1044 | 0.3678 |
Base model
HooshvareLab/bert-base-parsbert-uncased