dair-ai/emotion
Viewer • Updated • 437k • 17.9k • 457
How to use postgrammar/distilbert-base-uncased-finetuned-emotion with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="postgrammar/distilbert-base-uncased-finetuned-emotion") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("postgrammar/distilbert-base-uncased-finetuned-emotion")
model = AutoModelForSequenceClassification.from_pretrained("postgrammar/distilbert-base-uncased-finetuned-emotion", 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:
More information needed
More information needed
More information needed
The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.8209 | 1.0 | 250 | 0.3154 | 0.91 | 0.9081 |
| 0.2531 | 2.0 | 500 | 0.2204 | 0.9245 | 0.9244 |
Base model
distilbert/distilbert-base-uncased