Text Classification
Transformers
TensorBoard
Safetensors
roberta
Trained with AutoTrain
text-embeddings-inference
Instructions to use lomov/targetsandgoalsv1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lomov/targetsandgoalsv1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="lomov/targetsandgoalsv1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("lomov/targetsandgoalsv1") model = AutoModelForSequenceClassification.from_pretrained("lomov/targetsandgoalsv1") - Notebooks
- Google Colab
- Kaggle
Model Trained Using AutoTrain
- Problem type: Text Classification
Validation Metrics
loss: 0.22812850773334503
f1_macro: 0.928605054676046
f1_micro: 0.9313725490196079
f1_weighted: 0.9297769573887364
precision_macro: 0.9294524189261031
precision_micro: 0.9313725490196079
precision_weighted: 0.930390072030939
recall_macro: 0.93
recall_micro: 0.9313725490196079
recall_weighted: 0.9313725490196079
accuracy: 0.9313725490196079
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