metadata
license: mit
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: fedcsis-slot_baseline-xlm_r-en
results: []
fedcsis-slot_baseline-xlm_r-en
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: 0.1015
- Precision: 0.9723
- Recall: 0.9726
- F1: 0.9725
- Accuracy: 0.9860
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 |
|---|---|---|---|---|---|---|---|
| 1.2866 | 1.0 | 814 | 0.3188 | 0.8661 | 0.8672 | 0.8666 | 0.9250 |
| 0.1956 | 2.0 | 1628 | 0.1299 | 0.9409 | 0.9471 | 0.9440 | 0.9736 |
| 0.1063 | 3.0 | 2442 | 0.1196 | 0.9537 | 0.9607 | 0.9572 | 0.9810 |
| 0.0558 | 4.0 | 3256 | 0.0789 | 0.9661 | 0.9697 | 0.9679 | 0.9854 |
| 0.0367 | 5.0 | 4070 | 0.0824 | 0.9685 | 0.9690 | 0.9687 | 0.9848 |
| 0.031 | 6.0 | 4884 | 0.0887 | 0.9712 | 0.9728 | 0.9720 | 0.9859 |
| 0.0233 | 7.0 | 5698 | 0.0829 | 0.9736 | 0.9744 | 0.9740 | 0.9872 |
| 0.0139 | 8.0 | 6512 | 0.0879 | 0.9743 | 0.9747 | 0.9745 | 0.9876 |
| 0.007 | 9.0 | 7326 | 0.0978 | 0.9740 | 0.9734 | 0.9737 | 0.9870 |
| 0.0076 | 10.0 | 8140 | 0.1015 | 0.9723 | 0.9726 | 0.9725 | 0.9860 |
Framework versions
- Transformers 4.27.4
- Pytorch 1.13.1+cu116
- Datasets 2.11.0
- Tokenizers 0.13.2