cardiffnlp/tweet_eval
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How to use aXhyra/presentation_emotion_42 with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="aXhyra/presentation_emotion_42") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("aXhyra/presentation_emotion_42")
model = AutoModelForSequenceClassification.from_pretrained("aXhyra/presentation_emotion_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 |
|---|---|---|---|---|
| 0.3703 | 1.0 | 408 | 0.6624 | 0.7029 |
| 0.2122 | 2.0 | 816 | 0.6684 | 0.7258 |
| 0.9452 | 3.0 | 1224 | 1.0001 | 0.7041 |
| 0.0023 | 4.0 | 1632 | 1.0989 | 0.7329 |