community-datasets/yahoo_answers_topics
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How to use Prezily/distilbert-yahoo with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="Prezily/distilbert-yahoo") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("Prezily/distilbert-yahoo")
model = AutoModelForSequenceClassification.from_pretrained("Prezily/distilbert-yahoo")This model is a fine-tuned version of distilbert-base-uncased on the yahoo_answers_topics 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 |
|---|---|---|---|---|
| 1.0424 | 0.03 | 5000 | 1.0730 | 0.6706 |
| 1.0143 | 0.06 | 10000 | 1.0225 | 0.6793 |
| 0.9683 | 0.09 | 15000 | 0.9732 | 0.6950 |
| 0.8925 | 0.11 | 20000 | 0.9442 | 0.7038 |
| 0.9407 | 0.14 | 25000 | 0.9212 | 0.7090 |
| 0.9463 | 0.17 | 30000 | 0.9117 | 0.7124 |
Base model
distilbert/distilbert-base-uncased