nyu-mll/glue
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How to use aabidk/test-trainer with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="aabidk/test-trainer") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("aabidk/test-trainer")
model = AutoModelForSequenceClassification.from_pretrained("aabidk/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 | 0.3969 | 0.8186 | 0.8650 |
| 0.521 | 2.0 | 918 | 0.5370 | 0.8186 | 0.8791 |
| 0.3026 | 3.0 | 1377 | 0.6871 | 0.8578 | 0.9017 |