metadata
license: mit
base_model: xlm-roberta-large
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
model-index:
- name: xlmr-large-nli-indoindo
results: []
xlmr-large-nli-indoindo
This model is a fine-tuned version of xlm-roberta-large on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.3131
- Accuracy: 0.8584
- Precision: 0.8584
- Recall: 0.8584
- F1 Score: 0.8585
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: 1
- eval_batch_size: 1
- 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 Score |
|---|---|---|---|---|---|---|---|
| 1.449 | 1.0 | 10330 | 1.2228 | 0.7838 | 0.7838 | 0.7838 | 0.7810 |
| 1.2575 | 2.0 | 20660 | 1.1182 | 0.8257 | 0.8257 | 0.8257 | 0.8273 |
| 0.8123 | 3.0 | 30990 | 1.1538 | 0.8489 | 0.8489 | 0.8489 | 0.8488 |
| 0.6541 | 4.0 | 41320 | 1.1288 | 0.8562 | 0.8562 | 0.8562 | 0.8558 |
| 0.3653 | 5.0 | 51650 | 1.2424 | 0.8543 | 0.8543 | 0.8543 | 0.8544 |
| 0.3436 | 6.0 | 61980 | 1.3131 | 0.8584 | 0.8584 | 0.8584 | 0.8585 |
Framework versions
- Transformers 4.33.0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3