Text Classification
Transformers
TensorBoard
Safetensors
distilbert
Trained with AutoTrain
text-embeddings-inference
Instructions to use mserloth/distilbert-base-german-cased-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mserloth/distilbert-base-german-cased-v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mserloth/distilbert-base-german-cased-v1")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mserloth/distilbert-base-german-cased-v1") model = AutoModelForSequenceClassification.from_pretrained("mserloth/distilbert-base-german-cased-v1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Model Trained Using AutoTrain
- Problem type: Text Classification
Validation Metrics
loss: 0.4877149760723114
f1_macro: 0.7832535885167465
f1_micro: 0.780952380952381
f1_weighted: 0.7795579858737753
precision_macro: 0.764884597268017
precision_micro: 0.780952380952381
precision_weighted: 0.779495771931005
recall_macro: 0.8068884256321943
recall_micro: 0.780952380952381
recall_weighted: 0.780952380952381
accuracy: 0.780952380952381
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