cardiffnlp/tweet_eval
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How to use aXhyra/presentation_emotion_1234567 with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="aXhyra/presentation_emotion_1234567") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("aXhyra/presentation_emotion_1234567")
model = AutoModelForSequenceClassification.from_pretrained("aXhyra/presentation_emotion_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 |
|---|---|---|---|---|
| 0.1189 | 1.0 | 408 | 0.6827 | 0.7164 |
| 1.0678 | 2.0 | 816 | 0.6916 | 0.7396 |
| 0.6582 | 3.0 | 1224 | 0.9281 | 0.7276 |
| 0.0024 | 4.0 | 1632 | 1.0237 | 0.7273 |