cardiffnlp/tweet_eval
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How to use aXhyra/presentation_sentiment_31415 with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="aXhyra/presentation_sentiment_31415") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("aXhyra/presentation_sentiment_31415")
model = AutoModelForSequenceClassification.from_pretrained("aXhyra/presentation_sentiment_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 |
|---|---|---|---|---|
| 0.3747 | 1.0 | 11404 | 0.6515 | 0.7045 |
| 0.6511 | 2.0 | 22808 | 0.7334 | 0.7188 |
| 0.0362 | 3.0 | 34212 | 0.9498 | 0.7195 |
| 1.0576 | 4.0 | 45616 | 1.0860 | 0.7183 |