cardiffnlp/tweet_eval
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How to use aXhyra/sentiment_trained_42 with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="aXhyra/sentiment_trained_42") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("aXhyra/sentiment_trained_42")
model = AutoModelForSequenceClassification.from_pretrained("aXhyra/sentiment_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 |
|---|---|---|---|---|
| 0.6405 | 1.0 | 11404 | 0.6631 | 0.7046 |
| 0.5998 | 2.0 | 22808 | 0.8429 | 0.7102 |
| 0.5118 | 3.0 | 34212 | 1.0906 | 0.7155 |
| 0.3745 | 4.0 | 45616 | 1.3194 | 0.7132 |