cardiffnlp/tweet_eval
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How to use marcolatella/emotion_trained with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="marcolatella/emotion_trained") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("marcolatella/emotion_trained")
model = AutoModelForSequenceClassification.from_pretrained("marcolatella/emotion_trained")This model is a fine-tuned version of distilbert-base-uncased on the tweet_eval 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 | F1 |
|---|---|---|---|---|
| No log | 1.0 | 204 | 0.7468 | 0.6599 |
| No log | 2.0 | 408 | 0.6829 | 0.7369 |
| 0.5184 | 3.0 | 612 | 0.8089 | 0.7411 |
| 0.5184 | 4.0 | 816 | 0.9362 | 0.7378 |