metadata
license: mit
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: fedcsis-slot_baseline-xlm_r-es
results: []
fedcsis-slot_baseline-xlm_r-es
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: 0.0521
- Precision: 0.9728
- Recall: 0.9711
- F1: 0.9720
- Accuracy: 0.9914
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.7183 | 1.0 | 941 | 0.1287 | 0.9389 | 0.9429 | 0.9409 | 0.9802 |
| 0.0792 | 2.0 | 1882 | 0.0698 | 0.9551 | 0.9609 | 0.9580 | 0.9876 |
| 0.0502 | 3.0 | 2823 | 0.0586 | 0.9623 | 0.9624 | 0.9624 | 0.9886 |
| 0.0312 | 4.0 | 3764 | 0.0511 | 0.9697 | 0.9668 | 0.9682 | 0.9904 |
| 0.0229 | 5.0 | 4705 | 0.0494 | 0.9715 | 0.9687 | 0.9701 | 0.9913 |
| 0.021 | 6.0 | 5646 | 0.0447 | 0.9697 | 0.9680 | 0.9689 | 0.9911 |
| 0.0139 | 7.0 | 6587 | 0.0512 | 0.9715 | 0.9691 | 0.9703 | 0.9915 |
| 0.0126 | 8.0 | 7528 | 0.0507 | 0.9713 | 0.9699 | 0.9706 | 0.9913 |
| 0.01 | 9.0 | 8469 | 0.0500 | 0.9720 | 0.9702 | 0.9711 | 0.9913 |
| 0.0072 | 10.0 | 9410 | 0.0521 | 0.9728 | 0.9711 | 0.9720 | 0.9914 |
Framework versions
- Transformers 4.27.4
- Pytorch 1.13.1+cu116
- Datasets 2.11.0
- Tokenizers 0.13.2