nyu-mll/glue
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How to use gokuls/mobilebert_sa_GLUE_Experiment_cola_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_cola_256") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("gokuls/mobilebert_sa_GLUE_Experiment_cola_256")
model = AutoModelForSequenceClassification.from_pretrained("gokuls/mobilebert_sa_GLUE_Experiment_cola_256")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 |
|---|---|---|---|---|
| 0.6135 | 1.0 | 67 | 0.6178 | 0.0 |
| 0.6079 | 2.0 | 134 | 0.6178 | 0.0 |
| 0.6073 | 3.0 | 201 | 0.6181 | 0.0 |
| 0.6066 | 4.0 | 268 | 0.6167 | 0.0 |
| 0.6049 | 5.0 | 335 | 0.6144 | 0.0 |
| 0.5699 | 6.0 | 402 | 0.6194 | 0.1196 |
| 0.5015 | 7.0 | 469 | 0.6724 | 0.1179 |
| 0.4668 | 8.0 | 536 | 0.7723 | 0.1198 |
| 0.4425 | 9.0 | 603 | 0.7053 | 0.0810 |
| 0.4272 | 10.0 | 670 | 0.8389 | 0.1207 |