dair-ai/emotion
Viewer • Updated • 437k • 33.7k • 441
How to use V3RX2000/distilbert-base-uncased-finetuned-emotion with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="V3RX2000/distilbert-base-uncased-finetuned-emotion") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("V3RX2000/distilbert-base-uncased-finetuned-emotion")
model = AutoModelForSequenceClassification.from_pretrained("V3RX2000/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:
More information needed
More information needed
More information needed
The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.8812 | 1.0 | 250 | 0.3301 | 0.906 | 0.9035 |
| 0.2547 | 2.0 | 500 | 0.2285 | 0.9245 | 0.9247 |