nyu-mll/glue
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How to use 123abhiALFLKFO/distilbert-base-uncased-finetuned-cola with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="123abhiALFLKFO/distilbert-base-uncased-finetuned-cola") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("123abhiALFLKFO/distilbert-base-uncased-finetuned-cola")
model = AutoModelForSequenceClassification.from_pretrained("123abhiALFLKFO/distilbert-base-uncased-finetuned-cola", device_map="auto")This model is a fine-tuned version of distilbert-base-uncased 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 | Matthews Correlation |
|---|---|---|---|---|
| 0.5253 | 1.0 | 535 | 0.5214 | 0.3943 |
| 0.3459 | 2.0 | 1070 | 0.5551 | 0.4693 |
| 0.2326 | 3.0 | 1605 | 0.6371 | 0.5059 |
| 0.1718 | 4.0 | 2140 | 0.7851 | 0.5111 |
| 0.1262 | 5.0 | 2675 | 0.8628 | 0.5331 |