cardiffnlp/tweet_eval
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How to use aXhyra/irony_trained_42 with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="aXhyra/irony_trained_42") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("aXhyra/irony_trained_42")
model = AutoModelForSequenceClassification.from_pretrained("aXhyra/irony_trained_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 |
|---|---|---|---|---|
| 0.6669 | 1.0 | 716 | 0.6291 | 0.6198 |
| 0.5655 | 2.0 | 1432 | 0.7332 | 0.6771 |
| 0.3764 | 3.0 | 2148 | 1.4193 | 0.6554 |
| 0.229 | 4.0 | 2864 | 1.5669 | 0.6786 |