metadata
license: mit
base_model: xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: xlm-roberta-base-Mixed-aug_insert_vi
results: []
xlm-roberta-base-Mixed-aug_insert_vi
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: 0.5221
- Accuracy: 0.79
- F1: 0.7737
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 | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.9086 | 1.0 | 82 | 0.6185 | 0.79 | 0.7439 |
| 0.6351 | 2.0 | 164 | 0.4573 | 0.81 | 0.7858 |
| 0.4828 | 3.0 | 246 | 0.4669 | 0.79 | 0.7899 |
| 0.3772 | 4.0 | 328 | 0.4307 | 0.79 | 0.7676 |
| 0.2987 | 5.0 | 410 | 0.5221 | 0.79 | 0.7737 |
Framework versions
- Transformers 4.32.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3