metadata
license: mit
base_model: xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: xlmr-nli-indoindo
results: []
xlmr-nli-indoindo
This model is a fine-tuned version of xlm-roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6699
- Accuracy: 0.7701
- Precision: 0.7701
- Recall: 0.7701
- F1: 0.7693
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: 3e-06
- train_batch_size: 6
- eval_batch_size: 6
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 6
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 1.0444 | 1.0 | 1722 | 0.8481 | 0.6463 | 0.6463 | 0.6463 | 0.6483 |
| 0.7958 | 2.0 | 3444 | 0.7483 | 0.7369 | 0.7369 | 0.7369 | 0.7353 |
| 0.7175 | 3.0 | 5166 | 0.6812 | 0.7579 | 0.7579 | 0.7579 | 0.7576 |
| 0.66 | 4.0 | 6888 | 0.6293 | 0.7679 | 0.7679 | 0.7679 | 0.7674 |
| 0.6056 | 5.0 | 8610 | 0.6459 | 0.7651 | 0.7651 | 0.7651 | 0.7640 |
| 0.5769 | 6.0 | 10332 | 0.6699 | 0.7701 | 0.7701 | 0.7701 | 0.7693 |
Framework versions
- Transformers 4.31.0.dev0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3