legacy-datasets/banking77
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How to use Tingli/bert-base-banking77-pt2 with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="Tingli/bert-base-banking77-pt2") # pip install -U transformers accelerate
# Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("Tingli/bert-base-banking77-pt2")
model = AutoModelForSequenceClassification.from_pretrained("Tingli/bert-base-banking77-pt2", device_map="auto")This model is a fine-tuned version of bert-base-uncased on the banking77 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 | F1 |
|---|---|---|---|---|
| 1.0831 | 1.0 | 626 | 0.8018 | 0.8336 |
| 0.381 | 2.0 | 1252 | 0.3600 | 0.9206 |
| 0.1832 | 3.0 | 1878 | 0.2982 | 0.9292 |