cardiffnlp/tweet_eval
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How to use aXhyra/irony_trained with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="aXhyra/irony_trained") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("aXhyra/irony_trained")
model = AutoModelForSequenceClassification.from_pretrained("aXhyra/irony_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 |
|---|---|---|---|---|
| 0.6589 | 1.0 | 716 | 0.6187 | 0.6646 |
| 0.5494 | 2.0 | 1432 | 0.9314 | 0.6793 |
| 0.3369 | 3.0 | 2148 | 1.3468 | 0.6833 |
| 0.2129 | 4.0 | 2864 | 1.6471 | 0.6851 |