dair-ai/emotion
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How to use aliciiavs/distilbert-emotion with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="aliciiavs/distilbert-emotion") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("aliciiavs/distilbert-emotion")
model = AutoModelForSequenceClassification.from_pretrained("aliciiavs/distilbert-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 |
|---|---|---|---|---|
| No log | 1.0 | 250 | 0.1876 | 0.9295 |
| 0.3314 | 2.0 | 500 | 0.1371 | 0.939 |
Base model
distilbert/distilbert-base-uncased