dair-ai/emotion
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How to use elyadenysova/Emotion_DistilBert with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="elyadenysova/Emotion_DistilBert") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("elyadenysova/Emotion_DistilBert")
model = AutoModelForSequenceClassification.from_pretrained("elyadenysova/Emotion_DistilBert", device_map="auto")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 |
|---|---|---|---|---|
| 0.2358 | 1.0 | 1000 | 0.1881 | 0.928 |
| 0.1301 | 2.0 | 2000 | 0.1721 | 0.936 |
| 0.0806 | 3.0 | 3000 | 0.1738 | 0.94 |
Base model
distilbert/distilbert-base-uncased