nyu-mll/glue
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How to use rain1898/test-trainer2 with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="rain1898/test-trainer2") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("rain1898/test-trainer2")
model = AutoModelForSequenceClassification.from_pretrained("rain1898/test-trainer2")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 | 0.3636 | 0.8407 | 0.8837 |
| 0.5278 | 2.0 | 918 | 0.3803 | 0.8603 | 0.9002 |
| 0.3064 | 3.0 | 1377 | 0.5858 | 0.8775 | 0.9138 |
Base model
google-bert/bert-base-uncased