nyu-mll/glue
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How to use DipanAI/test_bug_temporary with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="DipanAI/test_bug_temporary") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("DipanAI/test_bug_temporary")
model = AutoModelForSequenceClassification.from_pretrained("DipanAI/test_bug_temporary")This model is a fine-tuned version of bert-base-cased on the glue 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 | Matthews Correlation |
|---|---|---|---|---|
| 0.4811 | 1.0 | 1069 | 0.5683 | 0.4612 |
| 0.3499 | 2.0 | 2138 | 0.5654 | 0.6041 |
| 0.1871 | 3.0 | 3207 | 0.8210 | 0.5914 |