cardiffnlp/tweet_eval
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How to use aXhyra/presentation_irony_42 with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="aXhyra/presentation_irony_42") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("aXhyra/presentation_irony_42")
model = AutoModelForSequenceClassification.from_pretrained("aXhyra/presentation_irony_42")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 |
|---|---|---|---|---|
| 0.6675 | 1.0 | 90 | 0.5988 | 0.6684 |
| 0.5872 | 2.0 | 180 | 0.6039 | 0.6742 |
| 0.3953 | 3.0 | 270 | 0.8549 | 0.6557 |
| 0.0355 | 4.0 | 360 | 0.9344 | 0.6745 |