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fine-tuned-IndoNLI-Basic-with-xlm-roberta-large-LR-3e-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: 1.1016
- Accuracy: 0.3409
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-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.06
- num_epochs: 16
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
1.1164 | 0.5 | 80 | 1.1892 | 0.2918 |
1.1255 | 0.99 | 160 | 1.1077 | 0.3409 |
1.1308 | 1.49 | 240 | 1.1054 | 0.3409 |
1.119 | 1.98 | 320 | 1.0943 | 0.3673 |
1.1218 | 2.48 | 400 | 1.1094 | 0.3673 |
1.1216 | 2.98 | 480 | 1.1402 | 0.2918 |
1.1149 | 3.48 | 560 | 1.1016 | 0.3409 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu117
- Datasets 2.2.0
- Tokenizers 0.13.2