nyu-mll/glue
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How to use gokuls/mobilebert_sa_GLUE_Experiment_sst2 with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="gokuls/mobilebert_sa_GLUE_Experiment_sst2") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("gokuls/mobilebert_sa_GLUE_Experiment_sst2")
model = AutoModelForSequenceClassification.from_pretrained("gokuls/mobilebert_sa_GLUE_Experiment_sst2")This model is a fine-tuned version of google/mobilebert-uncased on the GLUE SST2 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 | Accuracy |
|---|---|---|---|---|
| 0.487 | 1.0 | 527 | 0.4157 | 0.8028 |
| 0.2824 | 2.0 | 1054 | 0.4351 | 0.8005 |
| 0.2265 | 3.0 | 1581 | 0.4487 | 0.8096 |
| 0.1989 | 4.0 | 2108 | 0.5182 | 0.7993 |
| 0.1813 | 5.0 | 2635 | 0.4654 | 0.7982 |
| 0.1684 | 6.0 | 3162 | 0.5340 | 0.7924 |