nyu-mll/glue
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How to use gokuls/mobilebert_sa_GLUE_Experiment_data_aug_stsb_128 with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="gokuls/mobilebert_sa_GLUE_Experiment_data_aug_stsb_128") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("gokuls/mobilebert_sa_GLUE_Experiment_data_aug_stsb_128")
model = AutoModelForSequenceClassification.from_pretrained("gokuls/mobilebert_sa_GLUE_Experiment_data_aug_stsb_128")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 |
|---|---|---|---|---|---|---|
| 1.1017 | 1.0 | 2518 | 2.7704 | 0.1811 | 0.1984 | 0.1898 |
| 0.654 | 2.0 | 5036 | 3.0506 | 0.1580 | 0.1703 | 0.1642 |
| 0.5737 | 3.0 | 7554 | 3.1679 | 0.1482 | 0.1569 | 0.1526 |
| 0.4954 | 4.0 | 10072 | 3.3175 | 0.1564 | 0.1617 | 0.1590 |
| 0.3722 | 5.0 | 12590 | 2.9558 | 0.1426 | 0.1517 | 0.1471 |
| 0.276 | 6.0 | 15108 | 3.2021 | 0.1462 | 0.1530 | 0.1496 |