cardiffnlp/tweet_eval
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How to use mleli/my-awesome-model with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="mleli/my-awesome-model") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("mleli/my-awesome-model")
model = AutoModelForSequenceClassification.from_pretrained("mleli/my-awesome-model")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 | Accuracy |
|---|---|---|---|---|
| 0.0915 | 1.0 | 1490 | 1.3955 | 0.7689 |
| 0.0638 | 2.0 | 2980 | 1.5816 | 0.7621 |
| 0.024 | 3.0 | 4470 | 1.6838 | 0.7772 |