metadata
license: mit
base_model: xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: xlm-roberta-base-New_VietNam-aug_insert_synonym
results: []
xlm-roberta-base-New_VietNam-aug_insert_synonym
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: 1.0069
- Accuracy: 0.69
- F1: 0.7005
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: 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 | Accuracy | F1 |
|---|---|---|---|---|---|
| 1.0846 | 1.0 | 43 | 0.9691 | 0.59 | 0.4903 |
| 0.8237 | 2.0 | 86 | 0.7961 | 0.64 | 0.6370 |
| 0.6422 | 3.0 | 129 | 0.7569 | 0.71 | 0.7145 |
| 0.515 | 4.0 | 172 | 0.7775 | 0.71 | 0.7151 |
| 0.4099 | 5.0 | 215 | 0.8224 | 0.69 | 0.6970 |
| 0.3239 | 6.0 | 258 | 0.8941 | 0.69 | 0.7013 |
| 0.2709 | 7.0 | 301 | 0.8975 | 0.68 | 0.6907 |
| 0.2011 | 8.0 | 344 | 0.9745 | 0.7 | 0.7120 |
| 0.1795 | 9.0 | 387 | 1.0128 | 0.7 | 0.7120 |
| 0.158 | 10.0 | 430 | 1.0069 | 0.69 | 0.7005 |
Framework versions
- Transformers 4.32.1
- Pytorch 2.0.0
- Datasets 2.14.4
- Tokenizers 0.13.3