metadata
library_name: transformers
license: mit
base_model: FacebookAI/xlm-roberta-large
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: xlmr_immigration_combo27_1
results: []
xlmr_immigration_combo27_1
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: 0.1942
- Accuracy: 0.9357
- 1-f1: 0.8971
- 1-recall: 0.8417
- 1-precision: 0.9604
- Balanced Acc: 0.9122
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_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 15
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | 1-f1 | 1-recall | 1-precision | Balanced Acc |
|---|---|---|---|---|---|---|---|---|
| 0.2311 | 1.0 | 25 | 0.2019 | 0.9280 | 0.8819 | 0.8069 | 0.9721 | 0.8977 |
| 0.2538 | 2.0 | 50 | 0.1837 | 0.9383 | 0.9024 | 0.8571 | 0.9528 | 0.9180 |
| 0.1703 | 3.0 | 75 | 0.1974 | 0.9357 | 0.9016 | 0.8842 | 0.9197 | 0.9228 |
| 0.099 | 4.0 | 100 | 0.1942 | 0.9357 | 0.8971 | 0.8417 | 0.9604 | 0.9122 |
Framework versions
- Transformers 4.56.0.dev0
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.21.4