cardiffnlp/tweet_eval
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How to use aXhyra/hate_trained_31415 with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="aXhyra/hate_trained_31415") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("aXhyra/hate_trained_31415")
model = AutoModelForSequenceClassification.from_pretrained("aXhyra/hate_trained_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 |
|---|---|---|---|---|
| 0.482 | 1.0 | 563 | 0.4973 | 0.7672 |
| 0.3316 | 2.0 | 1126 | 0.4931 | 0.7794 |
| 0.2308 | 3.0 | 1689 | 0.7073 | 0.7593 |
| 0.1444 | 4.0 | 2252 | 0.8568 | 0.7729 |