cardiffnlp/tweet_eval
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How to use aXhyra/presentation_irony_31415 with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="aXhyra/presentation_irony_31415") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("aXhyra/presentation_irony_31415")
model = AutoModelForSequenceClassification.from_pretrained("aXhyra/presentation_irony_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 |
|---|---|---|---|---|
| 0.6601 | 1.0 | 90 | 0.6298 | 0.6230 |
| 0.4887 | 2.0 | 180 | 0.6039 | 0.6816 |
| 0.2543 | 3.0 | 270 | 0.7362 | 0.6803 |
| 0.1472 | 4.0 | 360 | 0.9694 | 0.6754 |