cardiffnlp/tweet_eval
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How to use aXhyra/irony_trained_1234567 with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="aXhyra/irony_trained_1234567") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("aXhyra/irony_trained_1234567")
model = AutoModelForSequenceClassification.from_pretrained("aXhyra/irony_trained_1234567")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 |
|---|---|---|---|---|
| 0.6608 | 1.0 | 716 | 0.6057 | 0.6704 |
| 0.5329 | 2.0 | 1432 | 0.8935 | 0.6621 |
| 0.3042 | 3.0 | 2148 | 1.3871 | 0.6822 |
| 0.1769 | 4.0 | 2864 | 1.6580 | 0.6766 |