Text Classification
Transformers
TensorBoard
Safetensors
roberta
Trained with AutoTrain
text-embeddings-inference
# Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("lomov/strategytransitionplanv1")
model = AutoModelForSequenceClassification.from_pretrained("lomov/strategytransitionplanv1", device_map="auto")Quick Links
Model Trained Using AutoTrain
- Problem type: Text Classification
Validation Metrics
loss: 0.12461505830287933
f1_macro: 0.9837010534684953
f1_micro: 0.9838709677419355
f1_weighted: 0.9838517321638102
precision_macro: 0.9848484848484849
precision_micro: 0.9838709677419355
precision_weighted: 0.9846041055718475
recall_macro: 0.9833333333333334
recall_micro: 0.9838709677419355
recall_weighted: 0.9838709677419355
accuracy: 0.9838709677419355
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="lomov/strategytransitionplanv1")