Text Classification
Transformers
TensorBoard
Safetensors
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use AnonymousCS/xlmr_spanish_immigration with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/xlmr_spanish_immigration with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/xlmr_spanish_immigration")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/xlmr_spanish_immigration") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/xlmr_spanish_immigration") - Notebooks
- Google Colab
- Kaggle
xlmr_spanish_immigration
This model is a fine-tuned version of FacebookAI/xlm-roberta-large on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2356
- Accuracy: 0.9231
- 1-f1: 0.8913
- 1-recall: 0.9535
- 1-precision: 0.8367
- Balanced Acc: 0.9308
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: 1e-05
- train_batch_size: 128
- eval_batch_size: 128
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | 1-f1 | 1-recall | 1-precision | Balanced Acc |
|---|---|---|---|---|---|---|---|---|
| 0.2922 | 1.0 | 5 | 0.1937 | 0.9308 | 0.9011 | 0.9535 | 0.8542 | 0.9365 |
| 0.0836 | 2.0 | 10 | 0.1749 | 0.9538 | 0.9302 | 0.9302 | 0.9302 | 0.9479 |
| 0.1733 | 3.0 | 15 | 0.1995 | 0.9462 | 0.9213 | 0.9535 | 0.8913 | 0.9480 |
| 0.0836 | 4.0 | 20 | 0.2356 | 0.9231 | 0.8913 | 0.9535 | 0.8367 | 0.9308 |
Framework versions
- Transformers 4.56.0.dev0
- Pytorch 2.6.0+cu124
- Datasets 4.0.0
- Tokenizers 0.21.4
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Model tree for AnonymousCS/xlmr_spanish_immigration
Base model
FacebookAI/xlm-roberta-large