dair-ai/emotion
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How to use XaviXva/distilbert-base-uncased-finetuned-emotion with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="XaviXva/distilbert-base-uncased-finetuned-emotion") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("XaviXva/distilbert-base-uncased-finetuned-emotion")
model = AutoModelForSequenceClassification.from_pretrained("XaviXva/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
This is only a test to get started with NLP and transformers. Just for fun!
More information needed
The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.8479 | 1.0 | 250 | 0.3281 | 0.894 | 0.8887 |
| 0.254 | 2.0 | 500 | 0.2179 | 0.9275 | 0.9273 |