dair-ai/emotion
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How to use radev/distilbert-base-uncased-finetuned-emotion with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="radev/distilbert-base-uncased-finetuned-emotion") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("radev/distilbert-base-uncased-finetuned-emotion")
model = AutoModelForSequenceClassification.from_pretrained("radev/distilbert-base-uncased-finetuned-emotion")This model is a fine-tuned version of distilbert-base-uncased on the emotion 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 | Accuracy | F1 |
|---|---|---|---|---|---|
| No log | 1.0 | 125 | 0.5816 | 0.8015 | 0.7597 |
| 0.7707 | 2.0 | 250 | 0.3645 | 0.8945 | 0.8872 |