Text Classification
Transformers
TensorBoard
Safetensors
bert
Trained with AutoTrain
text-embeddings-inference
Instructions to use Abgegrieft/toxicity-classifier-gaming with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Abgegrieft/toxicity-classifier-gaming with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Abgegrieft/toxicity-classifier-gaming")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Abgegrieft/toxicity-classifier-gaming") model = AutoModelForSequenceClassification.from_pretrained("Abgegrieft/toxicity-classifier-gaming") - Notebooks
- Google Colab
- Kaggle
Model Trained Using AutoTrain
- Problem type: Text Classification
Validation Metrics
loss: 0.17345599830150604
f1_macro: 0.7547155454831698
f1_micro: 0.9466019417475728
f1_weighted: 0.9445123807456527
precision_macro: 0.8558757528469544
precision_micro: 0.9466019417475728
precision_weighted: 0.9434254644943053
recall_macro: 0.6923009042209939
recall_micro: 0.9466019417475728
recall_weighted: 0.9466019417475728
accuracy: 0.9466019417475728
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Model tree for Abgegrieft/toxicity-classifier-gaming
Base model
google-bert/bert-base-german-cased