cardiffnlp/tweet_eval
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How to use aXhyra/demo_irony_42 with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="aXhyra/demo_irony_42", device_map="auto") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("aXhyra/demo_irony_42")
model = AutoModelForSequenceClassification.from_pretrained("aXhyra/demo_irony_42", device_map="auto")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 |
|---|---|---|---|---|
| No log | 1.0 | 358 | 0.5872 | 0.6786 |
| 0.5869 | 2.0 | 716 | 0.6884 | 0.6952 |
| 0.3417 | 3.0 | 1074 | 0.9824 | 0.6995 |
| 0.3417 | 4.0 | 1432 | 1.2905 | 0.6858 |