Text Classification
Transformers
TensorBoard
Safetensors
roberta
Trained with AutoTrain
text-embeddings-inference
Instructions to use lomov/strategydisofmaterialimpactsv1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lomov/strategydisofmaterialimpactsv1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="lomov/strategydisofmaterialimpactsv1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("lomov/strategydisofmaterialimpactsv1") model = AutoModelForSequenceClassification.from_pretrained("lomov/strategydisofmaterialimpactsv1") - Notebooks
- Google Colab
- Kaggle
Model Trained Using AutoTrain
- Problem type: Text Classification
Validation Metrics
loss: 0.4904100298881531
f1_macro: 0.851601435352396
f1_micro: 0.8658536585365854
f1_weighted: 0.8538194199208925
precision_macro: 0.8594329005283454
precision_micro: 0.8658536585365854
precision_weighted: 0.8606490578892111
recall_macro: 0.862797619047619
recall_micro: 0.8658536585365854
recall_weighted: 0.8658536585365854
accuracy: 0.8658536585365854
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