metadata
library_name: transformers
license: mit
base_model: xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: trigger_cls
results: []
trigger_cls
This model is a fine-tuned version of xlm-roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3221
- Accuracy: 0.8876
- Precision: 0.8878
- Recall: 0.8876
- F1: 0.8874
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: 32
- eval_batch_size: 32
- 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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 201 | 0.5449 | 0.8120 | 0.8036 | 0.8120 | 0.7961 |
| No log | 2.0 | 402 | 0.3569 | 0.8757 | 0.8766 | 0.8757 | 0.8736 |
| 0.7649 | 3.0 | 603 | 0.3444 | 0.8826 | 0.8831 | 0.8826 | 0.8822 |
| 0.7649 | 4.0 | 804 | 0.3337 | 0.8832 | 0.8836 | 0.8832 | 0.8830 |
| 0.2524 | 5.0 | 1005 | 0.3221 | 0.8876 | 0.8878 | 0.8876 | 0.8874 |
Framework versions
- Transformers 4.52.4
- Pytorch 2.7.1+cu126
- Datasets 4.0.0
- Tokenizers 0.21.1