dair-ai/emotion
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How to use mudogruer/roberta-emotion with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="mudogruer/roberta-emotion") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("mudogruer/roberta-emotion")
model = AutoModelForSequenceClassification.from_pretrained("mudogruer/roberta-emotion")# Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("mudogruer/roberta-emotion")
model = AutoModelForSequenceClassification.from_pretrained("mudogruer/roberta-emotion")This model is a fine-tuned version of roberta-base 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 |
|---|---|---|---|---|
| 0.6103 | 1.0 | 500 | 0.2516 | 0.9195 |
| 0.1981 | 2.0 | 1000 | 0.1747 | 0.9345 |
| 0.1214 | 3.0 | 1500 | 0.1394 | 0.938 |
Base model
FacebookAI/roberta-base
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mudogruer/roberta-emotion")