metadata
license: mit
base_model: xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: result
results: []
result
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: 0.8753
- Accuracy: 0.7905
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: 8
- eval_batch_size: 8
- 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 |
|---|---|---|---|---|
| 0.5769 | 1.0 | 12925 | 0.6333 | 0.7682 |
| 0.4925 | 2.0 | 25850 | 0.5946 | 0.7824 |
| 0.43 | 3.0 | 38775 | 0.5930 | 0.7864 |
| 0.3766 | 4.0 | 51700 | 0.6989 | 0.7905 |
| 0.3333 | 5.0 | 64625 | 0.8753 | 0.7905 |
Framework versions
- Transformers 4.35.0
- Pytorch 2.0.0
- Datasets 2.11.0
- Tokenizers 0.14.1