Text Classification
Transformers
Safetensors
PyTorch
Portuguese
modernbert
binary-classification
Eval Results (legacy)
text-embeddings-inference
Instructions to use tcepi/prog_integridade_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tcepi/prog_integridade_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tcepi/prog_integridade_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tcepi/prog_integridade_model") model = AutoModelForSequenceClassification.from_pretrained("tcepi/prog_integridade_model") - Notebooks
- Google Colab
- Kaggle
Add training results
Browse files- train_results.json +5 -5
train_results.json
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{
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"epoch": 10.0,
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"total_flos":
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"train_loss": 0.
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"train_runtime":
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"train_samples_per_second":
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"train_steps_per_second":
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{
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"epoch": 10.0,
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"total_flos": 2.62042783586304e+16,
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"train_loss": 0.07008712296674256,
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"train_runtime": 2731.9046,
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"train_samples_per_second": 14.074,
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"train_steps_per_second": 1.761
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}
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