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xlm-roberta-base-finetuned-TRAC-DS
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: 1.0206
- Accuracy: 0.6814
- Precision: 0.6561
- Recall: 0.6528
- F1: 0.6543
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: 8
- eval_batch_size: 16
- seed: 43
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 6
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
---|---|---|---|---|---|---|---|
0.9928 | 0.5 | 612 | 0.9026 | 0.6201 | 0.5845 | 0.5812 | 0.5809 |
0.8756 | 1.0 | 1224 | 0.7883 | 0.6373 | 0.6358 | 0.6382 | 0.6251 |
0.7793 | 1.5 | 1836 | 0.8551 | 0.6340 | 0.6226 | 0.6368 | 0.6020 |
0.7667 | 2.0 | 2448 | 0.7861 | 0.6618 | 0.6518 | 0.6637 | 0.6442 |
0.6619 | 2.5 | 3060 | 0.8597 | 0.6887 | 0.6662 | 0.6472 | 0.6503 |
0.6786 | 3.0 | 3672 | 0.7905 | 0.6634 | 0.6587 | 0.6658 | 0.6513 |
0.573 | 3.5 | 4284 | 0.9263 | 0.6797 | 0.6575 | 0.6488 | 0.6514 |
0.5805 | 4.0 | 4896 | 0.8351 | 0.6944 | 0.6719 | 0.6740 | 0.6723 |
0.5069 | 4.5 | 5508 | 0.9772 | 0.6748 | 0.6564 | 0.6572 | 0.6546 |
0.5085 | 5.0 | 6120 | 1.0206 | 0.6814 | 0.6561 | 0.6528 | 0.6543 |
Framework versions
- Transformers 4.20.1
- Pytorch 1.10.1+cu111
- Datasets 2.3.2
- Tokenizers 0.12.1