nyu-mll/glue
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How to use muhtasham/bert-tiny-finetuned-glue-rte with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="muhtasham/bert-tiny-finetuned-glue-rte") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("muhtasham/bert-tiny-finetuned-glue-rte")
model = AutoModelForSequenceClassification.from_pretrained("muhtasham/bert-tiny-finetuned-glue-rte")This model is a fine-tuned version of google/bert_uncased_L-2_H-128_A-2 on the glue 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 |
|---|---|---|---|---|
| No log | 1.0 | 156 | 0.6852 | 0.5776 |
| No log | 2.0 | 312 | 0.6800 | 0.5993 |
| No log | 3.0 | 468 | 0.6737 | 0.6173 |
| 0.6845 | 4.0 | 624 | 0.6690 | 0.6101 |
| 0.6845 | 5.0 | 780 | 0.6673 | 0.6318 |