metadata
license: mit
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: xlm-roberta-base-finetuned-pos
results: []
xlm-roberta-base-finetuned-pos
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: 0.0683
- Precision: 0.9800
- Recall: 0.9819
- F1: 0.9809
- Accuracy: 0.9822
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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.1542 | 1.0 | 1583 | 0.1251 | 0.9526 | 0.9613 | 0.9569 | 0.9622 |
| 0.0953 | 2.0 | 3166 | 0.0813 | 0.9725 | 0.9750 | 0.9737 | 0.9763 |
| 0.0694 | 3.0 | 4749 | 0.0707 | 0.9765 | 0.9792 | 0.9778 | 0.9797 |
| 0.0497 | 4.0 | 6332 | 0.0684 | 0.9784 | 0.9809 | 0.9796 | 0.9814 |
| 0.0435 | 5.0 | 7915 | 0.0683 | 0.9800 | 0.9819 | 0.9809 | 0.9822 |
Framework versions
- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3