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xlm-roberta-base-finetuned-on-REDv2
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: 0.3089
- F1: 0.6515
- Roc Auc: 0.7862
- Accuracy: 0.5506
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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- 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 | F1 | Roc Auc | Accuracy |
|---|---|---|---|---|---|---|
| No log | 1.0 | 255 | 0.3295 | 0.4028 | 0.6293 | 0.2615 |
| 0.3619 | 2.0 | 511 | 0.2778 | 0.6014 | 0.7346 | 0.4678 |
| 0.3619 | 3.0 | 766 | 0.2667 | 0.6509 | 0.7781 | 0.5488 |
| 0.2296 | 4.0 | 1022 | 0.2640 | 0.6466 | 0.7745 | 0.5433 |
| 0.2296 | 5.0 | 1277 | 0.2791 | 0.6432 | 0.7775 | 0.5414 |
| 0.1639 | 6.0 | 1533 | 0.2896 | 0.6354 | 0.7743 | 0.5414 |
| 0.1639 | 7.0 | 1788 | 0.2895 | 0.6519 | 0.7838 | 0.5635 |
| 0.1213 | 8.0 | 2044 | 0.2984 | 0.6457 | 0.7811 | 0.5525 |
| 0.1213 | 9.0 | 2299 | 0.3082 | 0.6474 | 0.7821 | 0.5562 |
| 0.0975 | 9.98 | 2550 | 0.3089 | 0.6515 | 0.7862 | 0.5506 |
Framework versions
- Transformers 4.27.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2
