nyu-mll/glue
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How to use gokuls/mobilebert_sa_GLUE_Experiment_stsb with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="gokuls/mobilebert_sa_GLUE_Experiment_stsb") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("gokuls/mobilebert_sa_GLUE_Experiment_stsb")
model = AutoModelForSequenceClassification.from_pretrained("gokuls/mobilebert_sa_GLUE_Experiment_stsb")This model is a fine-tuned version of google/mobilebert-uncased on the GLUE STSB 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 | Pearson | Spearmanr | Combined Score |
|---|---|---|---|---|---|---|
| 4.0455 | 1.0 | 45 | 2.3024 | 0.0671 | 0.0815 | 0.0743 |
| 2.1712 | 2.0 | 90 | 2.6644 | 0.0612 | 0.0724 | 0.0668 |
| 2.0637 | 3.0 | 135 | 2.3625 | 0.0582 | 0.0669 | 0.0625 |
| 1.996 | 4.0 | 180 | 2.8671 | 0.0713 | 0.0728 | 0.0720 |
| 1.908 | 5.0 | 225 | 2.6622 | 0.0954 | 0.0898 | 0.0926 |
| 1.7068 | 6.0 | 270 | 2.3885 | 0.1998 | 0.2006 | 0.2002 |