Toygar/turkish-offensive-language-detection
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How to use atakanince/distilbert-base-uncased-turkish-offensiveLanguage-v1 with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="atakanince/distilbert-base-uncased-turkish-offensiveLanguage-v1") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("atakanince/distilbert-base-uncased-turkish-offensiveLanguage-v1")
model = AutoModelForSequenceClassification.from_pretrained("atakanince/distilbert-base-uncased-turkish-offensiveLanguage-v1")This model is a fine-tuned version of distilbert/distilbert-base-uncased on the Turkish Offensive Language Dataset 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 |
|---|---|---|---|---|
| 0.3075 | 0.36 | 1000 | 0.2871 | 0.8901 |
| 0.2652 | 0.72 | 2000 | 0.2520 | 0.9031 |
| 0.2825 | 1.09 | 3000 | 0.2506 | 0.9007 |
| 0.2471 | 1.45 | 4000 | 0.2440 | 0.9067 |
Base model
distilbert/distilbert-base-uncased