cardiffnlp/tweet_eval
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How to use aXhyra/demo_emotion_42 with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="aXhyra/demo_emotion_42") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("aXhyra/demo_emotion_42")
model = AutoModelForSequenceClassification.from_pretrained("aXhyra/demo_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 |
|---|---|---|---|---|
| No log | 1.0 | 204 | 0.7431 | 0.6530 |
| No log | 2.0 | 408 | 0.6943 | 0.7333 |
| 0.5176 | 3.0 | 612 | 0.8456 | 0.7326 |
| 0.5176 | 4.0 | 816 | 0.9818 | 0.7348 |