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fine-tuned-IndoNLI-Translated-with-xlm-roberta-large-LR-1e-05
This model is a fine-tuned version of xlm-roberta-large on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4945
- Accuracy: 0.8553
- F1: 0.8555
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: 1e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 128
- 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 |
|---|---|---|---|---|---|
| 0.4916 | 0.5 | 1533 | 0.4336 | 0.8335 | 0.8342 |
| 0.4465 | 1.0 | 3066 | 0.4120 | 0.8454 | 0.8463 |
| 0.3666 | 1.5 | 4599 | 0.4001 | 0.8537 | 0.8538 |
| 0.3876 | 2.0 | 6132 | 0.3928 | 0.8530 | 0.8528 |
| 0.3347 | 2.5 | 7665 | 0.4415 | 0.8502 | 0.8505 |
| 0.3372 | 3.0 | 9198 | 0.4174 | 0.8582 | 0.8583 |
| 0.2641 | 3.5 | 10731 | 0.4568 | 0.8532 | 0.8529 |
| 0.2747 | 4.0 | 12264 | 0.4262 | 0.8576 | 0.8577 |
| 0.231 | 4.5 | 13797 | 0.4945 | 0.8553 | 0.8555 |
Framework versions
- Transformers 4.29.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.2.0
- Tokenizers 0.13.2
