nyu-mll/glue
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How to use xysmalobia/test-trainer with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="xysmalobia/test-trainer") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("xysmalobia/test-trainer")
model = AutoModelForSequenceClassification.from_pretrained("xysmalobia/test-trainer")This model is a fine-tuned version of bert-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 | Accuracy | F1 |
|---|---|---|---|---|---|
| No log | 1.0 | 459 | 0.4443 | 0.8039 | 0.8485 |
| 0.5584 | 2.0 | 918 | 0.3841 | 0.8431 | 0.8810 |
| 0.3941 | 3.0 | 1377 | 0.5802 | 0.8505 | 0.8935 |
Base model
google-bert/bert-base-uncased