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fine-tuned-IndoNLI-Basic-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: 0.9957
- Accuracy: 0.4479
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: 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 |
---|---|---|---|---|
1.1281 | 0.5 | 80 | 1.1390 | 0.2918 |
1.1242 | 0.99 | 160 | 1.1046 | 0.2918 |
1.1299 | 1.49 | 240 | 1.1121 | 0.3409 |
1.1122 | 1.98 | 320 | 1.0952 | 0.3673 |
1.1135 | 2.48 | 400 | 1.1079 | 0.3673 |
1.1105 | 2.98 | 480 | 1.1132 | 0.2918 |
1.0599 | 3.48 | 560 | 1.0510 | 0.4706 |
1.0581 | 3.97 | 640 | 1.0231 | 0.4998 |
1.0079 | 4.47 | 720 | 0.9927 | 0.4492 |
1.005 | 4.97 | 800 | 0.9988 | 0.4479 |
1.0051 | 5.46 | 880 | 0.9903 | 0.5198 |
1.0087 | 5.96 | 960 | 0.9857 | 0.5175 |
1.0148 | 6.46 | 1040 | 1.0094 | 0.4483 |
0.9969 | 6.95 | 1120 | 0.9957 | 0.4479 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu117
- Datasets 2.2.0
- Tokenizers 0.13.2