Text Classification
Transformers
TensorBoard
Safetensors
roberta
Trained with AutoTrain
text-embeddings-inference
Instructions to use SamanthaStorm/Tether2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SamanthaStorm/Tether2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="SamanthaStorm/Tether2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("SamanthaStorm/Tether2") model = AutoModelForSequenceClassification.from_pretrained("SamanthaStorm/Tether2") - Notebooks
- Google Colab
- Kaggle
Model Trained Using AutoTrain
- Problem type: Text Classification
Validation Metrics
loss: 1.0832968950271606
f1_macro: 0.41533378210893174
f1_micro: 0.6531007751937985
f1_weighted: 0.6340857128792562
precision_macro: 0.43774810378738616
precision_micro: 0.6531007751937985
precision_weighted: 0.6386639752005375
recall_macro: 0.4299005706500963
recall_micro: 0.6531007751937985
recall_weighted: 0.6531007751937985
accuracy: 0.6531007751937985
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Model tree for SamanthaStorm/Tether2
Base model
FacebookAI/roberta-base