Text Classification
Transformers
TensorBoard
Safetensors
roberta
Trained with AutoTrain
text-embeddings-inference
Instructions to use guess-winnow/autotrain-j9jny-iiqet with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use guess-winnow/autotrain-j9jny-iiqet with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="guess-winnow/autotrain-j9jny-iiqet")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("guess-winnow/autotrain-j9jny-iiqet") model = AutoModelForSequenceClassification.from_pretrained("guess-winnow/autotrain-j9jny-iiqet", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Model Trained Using AutoTrain
- Problem type: Text Classification
Validation Metrics
loss: 0.929474949836731
f1_macro: 0.6082092997869687
f1_micro: 0.7263610315186246
f1_weighted: 0.7155925161484715
precision_macro: 0.6156993792258936
precision_micro: 0.7263610315186246
precision_weighted: 0.7206864924688222
recall_macro: 0.6223040013057595
recall_micro: 0.7263610315186246
recall_weighted: 0.7263610315186246
accuracy: 0.7263610315186246
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Model tree for guess-winnow/autotrain-j9jny-iiqet
Base model
mrm8488/longformer-base-4096-spanish