nyu-mll/glue
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How to use vicl/canine-c-finetuned-mrpc with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="vicl/canine-c-finetuned-mrpc") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("vicl/canine-c-finetuned-mrpc")
model = AutoModelForSequenceClassification.from_pretrained("vicl/canine-c-finetuned-mrpc")This model is a fine-tuned version of google/canine-c 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 | F1 |
|---|---|---|---|---|---|
| No log | 1.0 | 230 | 0.5014 | 0.7696 | 0.8479 |
| No log | 2.0 | 460 | 0.4755 | 0.7892 | 0.8622 |
| 0.5096 | 3.0 | 690 | 0.3645 | 0.8431 | 0.8869 |
| 0.5096 | 4.0 | 920 | 0.4066 | 0.8627 | 0.9014 |
| 0.2619 | 5.0 | 1150 | 0.4551 | 0.8431 | 0.8877 |