Text Classification
Transformers
Safetensors
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use Maldak123/roberta-reunioes-risco-churn with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Maldak123/roberta-reunioes-risco-churn with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Maldak123/roberta-reunioes-risco-churn")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Maldak123/roberta-reunioes-risco-churn") model = AutoModelForSequenceClassification.from_pretrained("Maldak123/roberta-reunioes-risco-churn", device_map="auto") - Notebooks
- Google Colab
- Kaggle
roberta-reunioes-risco-churn
This model is a fine-tuned version of FacebookAI/xlm-roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0000
- Accuracy: 1.0
- Precision Weighted: 1.0
- Recall Weighted: 1.0
- F1 Weighted: 1.0
- F1 Macro: 1.0
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- total_eval_batch_size: 16
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 4.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision Weighted | Recall Weighted | F1 Weighted | F1 Macro |
|---|---|---|---|---|---|---|---|---|
| 0.0002 | 1.0 | 300 | 0.0001 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0001 | 2.0 | 600 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0001 | 3.0 | 900 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
Framework versions
- Transformers 4.57.6
- Pytorch 2.11.0+cu128
- Datasets 4.8.5
- Tokenizers 0.22.2
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Model tree for Maldak123/roberta-reunioes-risco-churn
Base model
FacebookAI/xlm-roberta-base