Text Classification
Transformers
TensorBoard
Safetensors
deberta-v2
Trained with AutoTrain
text-embeddings-inference
# Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("luukschmitz/Geodeberta2")
model = AutoModelForSequenceClassification.from_pretrained("luukschmitz/Geodeberta2", device_map="auto")Quick Links
Model Trained Using AutoTrain
- Problem type: Text Classification
Validation Metrics
loss: 0.9531590342521667
f1_macro: 0.4940971741477817
f1_micro: 0.6548117154811716
f1_weighted: 0.628735443682528
precision_macro: 0.6898690717515761
precision_micro: 0.6548117154811716
precision_weighted: 0.6835107777099136
recall_macro: 0.47932568993970953
recall_micro: 0.6548117154811716
recall_weighted: 0.6548117154811716
accuracy: 0.6548117154811716
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Model tree for luukschmitz/Geodeberta2
Base model
microsoft/deberta-v3-base
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="luukschmitz/Geodeberta2")