dair-ai/emotion
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How to use mehmettozlu/distilbert-base-uncased with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="mehmettozlu/distilbert-base-uncased") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("mehmettozlu/distilbert-base-uncased")
model = AutoModelForSequenceClassification.from_pretrained("mehmettozlu/distilbert-base-uncased", 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 |
|---|---|---|---|---|
| No log | 1.0 | 250 | 0.1900 | 0.932 |
| 0.3456 | 2.0 | 500 | 0.1357 | 0.936 |
| 0.3456 | 3.0 | 750 | 0.1391 | 0.9445 |
| 0.0865 | 4.0 | 1000 | 0.1422 | 0.9455 |
| 0.0865 | 5.0 | 1250 | 0.1508 | 0.9415 |
Base model
distilbert/distilbert-base-uncased