Text Classification
Transformers
TensorBoard
Safetensors
bert
Trained with AutoTrain
text-embeddings-inference
Instructions to use Deepalipp/autotrain-mjmkb-qhqe4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Deepalipp/autotrain-mjmkb-qhqe4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Deepalipp/autotrain-mjmkb-qhqe4")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Deepalipp/autotrain-mjmkb-qhqe4") model = AutoModelForSequenceClassification.from_pretrained("Deepalipp/autotrain-mjmkb-qhqe4") - Notebooks
- Google Colab
- Kaggle
Model Trained Using AutoTrain
- Problem type: Text Classification
Validation Metrics
loss: 1.731958270072937
f1_macro: 0.3095238095238095
f1_micro: 0.42857142857142855
f1_weighted: 0.3095238095238095
precision_macro: 0.2619047619047619
precision_micro: 0.42857142857142855
precision_weighted: 0.2619047619047619
recall_macro: 0.42857142857142855
recall_micro: 0.42857142857142855
recall_weighted: 0.42857142857142855
accuracy: 0.42857142857142855
- Downloads last month
- 2
Model tree for Deepalipp/autotrain-mjmkb-qhqe4
Base model
google-bert/bert-base-uncased