metadata
library_name: transformers
license: mit
base_model: FacebookAI/xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: Roberta_monant
results: []
Roberta_monant
This model is a fine-tuned version of FacebookAI/xlm-roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4024
- Accuracy: 0.836
- Auc: 0.739
- Precision: 0.0
- Recall: 0.0
- F1: 0.0
- F1-macro: 0.455
- F1-micro: 0.836
- F1-weighted: 0.761
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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_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
- num_epochs: 2
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Auc | Precision | Recall | F1 | F1-macro | F1-micro | F1-weighted |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.5476 | 0.8475 | 50 | 0.4161 | 0.836 | 0.693 | 0.0 | 0.0 | 0.0 | 0.455 | 0.836 | 0.761 |
| 0.4961 | 1.6949 | 100 | 0.4024 | 0.836 | 0.739 | 0.0 | 0.0 | 0.0 | 0.455 | 0.836 | 0.761 |
Framework versions
- Transformers 4.55.2
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.21.4