nyu-mll/glue
Viewer • Updated • 1.49M • 485k • 500
How to use gokuls/mobilebert_sa_GLUE_Experiment_data_aug_sst2_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_sst2_128") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("gokuls/mobilebert_sa_GLUE_Experiment_data_aug_sst2_128")
model = AutoModelForSequenceClassification.from_pretrained("gokuls/mobilebert_sa_GLUE_Experiment_data_aug_sst2_128")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:
More information needed
More information needed
More information needed
The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.3587 | 1.0 | 8748 | 0.4922 | 0.7936 |
| 0.2861 | 2.0 | 17496 | 0.5522 | 0.7878 |
| 0.2387 | 3.0 | 26244 | 0.7233 | 0.7775 |
| 0.2089 | 4.0 | 34992 | 0.6891 | 0.7890 |
| 0.1882 | 5.0 | 43740 | 0.8317 | 0.7913 |
| 0.1726 | 6.0 | 52488 | 0.8467 | 0.7706 |