legacy-datasets/banking77
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How to use YUCHUL/bert-base-enth77-banking-pt2 with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="YUCHUL/bert-base-enth77-banking-pt2") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("YUCHUL/bert-base-enth77-banking-pt2")
model = AutoModelForSequenceClassification.from_pretrained("YUCHUL/bert-base-enth77-banking-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 |
|---|---|---|---|---|
| 1.1775 | 1.0 | 626 | 0.8671 | 0.8176 |
| 0.4114 | 2.0 | 1252 | 0.3822 | 0.9156 |
| 0.1987 | 3.0 | 1878 | 0.3131 | 0.9232 |