nyu-mll/glue
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How to use gokuls/mobilebert_sa_GLUE_Experiment_cola with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="gokuls/mobilebert_sa_GLUE_Experiment_cola") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("gokuls/mobilebert_sa_GLUE_Experiment_cola")
model = AutoModelForSequenceClassification.from_pretrained("gokuls/mobilebert_sa_GLUE_Experiment_cola")This model is a fine-tuned version of google/mobilebert-uncased on the GLUE COLA 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 |
|---|---|---|---|---|
| 0.6122 | 1.0 | 67 | 0.6184 | 0.0 |
| 0.6078 | 2.0 | 134 | 0.6180 | 0.0 |
| 0.607 | 3.0 | 201 | 0.6185 | 0.0 |
| 0.6052 | 4.0 | 268 | 0.6153 | 0.0 |
| 0.5822 | 5.0 | 335 | 0.6292 | 0.0506 |
| 0.5193 | 6.0 | 402 | 0.6422 | 0.0743 |
| 0.4783 | 7.0 | 469 | 0.7020 | 0.0629 |
| 0.4504 | 8.0 | 536 | 0.7422 | 0.0834 |
| 0.4315 | 9.0 | 603 | 0.6915 | 0.0812 |