cardiffnlp/tweet_eval
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How to use aXhyra/presentation_emotion_31415 with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="aXhyra/presentation_emotion_31415") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("aXhyra/presentation_emotion_31415")
model = AutoModelForSequenceClassification.from_pretrained("aXhyra/presentation_emotion_31415")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 |
|---|---|---|---|---|
| 0.73 | 1.0 | 408 | 0.8206 | 0.6491 |
| 0.3868 | 2.0 | 816 | 0.7733 | 0.7230 |
| 0.0639 | 3.0 | 1224 | 0.9962 | 0.7101 |
| 0.0507 | 4.0 | 1632 | 1.1243 | 0.7149 |