nyu-mll/glue
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How to use gokuls/mobilebert_sa_GLUE_Experiment_stsb_256 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_256") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("gokuls/mobilebert_sa_GLUE_Experiment_stsb_256")
model = AutoModelForSequenceClassification.from_pretrained("gokuls/mobilebert_sa_GLUE_Experiment_stsb_256")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 |
|---|---|---|---|---|---|---|
| 4.155 | 1.0 | 45 | 2.2966 | 0.0077 | 0.0083 | 0.0080 |
| 2.1654 | 2.0 | 90 | 2.3384 | 0.0600 | 0.0633 | 0.0616 |
| 2.0822 | 3.0 | 135 | 2.3583 | 0.0625 | 0.0718 | 0.0671 |
| 2.0017 | 4.0 | 180 | 2.7680 | 0.0721 | 0.0753 | 0.0737 |
| 1.9379 | 5.0 | 225 | 2.7330 | 0.0963 | 0.0919 | 0.0941 |
| 1.785 | 6.0 | 270 | 2.3938 | 0.1605 | 0.1497 | 0.1551 |