nyu-mll/glue
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How to use gokuls/mobilebert_add_GLUE_Experiment_cola with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="gokuls/mobilebert_add_GLUE_Experiment_cola") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("gokuls/mobilebert_add_GLUE_Experiment_cola")
model = AutoModelForSequenceClassification.from_pretrained("gokuls/mobilebert_add_GLUE_Experiment_cola", device_map="auto")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 |
|---|---|---|---|---|
| 0.6126 | 1.0 | 67 | 0.6183 | 0.0 |
| 0.6078 | 2.0 | 134 | 0.6179 | 0.0 |
| 0.6072 | 3.0 | 201 | 0.6183 | 0.0 |
| 0.6062 | 4.0 | 268 | 0.6164 | 0.0 |
| 0.601 | 5.0 | 335 | 0.6127 | 0.0 |
| 0.5928 | 6.0 | 402 | 0.6148 | 0.0 |
| 0.588 | 7.0 | 469 | 0.6224 | 0.0 |
| 0.582 | 8.0 | 536 | 0.6174 | 0.0029 |
| 0.5807 | 9.0 | 603 | 0.6301 | 0.0029 |
| 0.5743 | 10.0 | 670 | 0.6156 | 0.0438 |