Text Classification
Transformers
TensorBoard
Safetensors
bert
Trained with AutoTrain
text-embeddings-inference
# Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("luukschmitz/GeoBERT")
model = AutoModelForSequenceClassification.from_pretrained("luukschmitz/GeoBERT", device_map="auto")Quick Links
Model Trained Using AutoTrain
- Problem type: Text Classification
Validation Metrics
loss: 0.9093852639198303
f1_macro: 0.5823605917694434
f1_micro: 0.6589958158995816
f1_weighted: 0.6565370798157575
precision_macro: 0.6115906152670858
precision_micro: 0.6589958158995816
precision_weighted: 0.6611483212824585
recall_macro: 0.5656902456694988
recall_micro: 0.6589958158995816
recall_weighted: 0.6589958158995816
accuracy: 0.6589958158995816
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="luukschmitz/GeoBERT")