dair-ai/emotion
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How to use grantsl/distilbert-base-uncased-finetuned-emotion with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="grantsl/distilbert-base-uncased-finetuned-emotion") # pip install -U transformers accelerate
# Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("grantsl/distilbert-base-uncased-finetuned-emotion")
model = AutoModelForSequenceClassification.from_pretrained("grantsl/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:
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The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.436 | 1.0 | 2000 | 0.2178 | 0.93 | 0.9305 |
| 0.1615 | 2.0 | 4000 | 0.1764 | 0.9415 | 0.9415 |