odegiber/hate_speech18
Updated โข 1k โข 17
How to use Narrativaai/deberta-v3-small-finetuned-hate_speech18 with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="Narrativaai/deberta-v3-small-finetuned-hate_speech18") # pip install -U transformers accelerate
# Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("Narrativaai/deberta-v3-small-finetuned-hate_speech18")
model = AutoModelForSequenceClassification.from_pretrained("Narrativaai/deberta-v3-small-finetuned-hate_speech18", device_map="auto")This model is a fine-tuned version of microsoft/deberta-v3-small on the hate_speech18 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 |
|---|---|---|---|---|
| 0.4147 | 1.0 | 650 | 0.3910 | 0.8832 |
| 0.2975 | 2.0 | 1300 | 0.2922 | 0.9161 |
| 0.2575 | 3.0 | 1950 | 0.3555 | 0.9051 |
| 0.1553 | 4.0 | 2600 | 0.4263 | 0.9124 |
| 0.1267 | 5.0 | 3250 | 0.4238 | 0.9161 |