nyu-mll/glue
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How to use antoinerossupedu/bert-playground with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="antoinerossupedu/bert-playground") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("antoinerossupedu/bert-playground")
model = AutoModelForSequenceClassification.from_pretrained("antoinerossupedu/bert-playground")This model is a fine-tuned version of bert-base-cased 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 |
|---|---|---|---|---|
| 0.4401 | 1.0 | 1069 | 0.4155 | 0.5720 |
| 0.3121 | 2.0 | 2138 | 0.6457 | 0.6039 |
| 0.1764 | 3.0 | 3207 | 0.8178 | 0.6068 |
Base model
google-bert/bert-base-cased