xlm-roberta-profane-final
This model is a fine-tuned version of xlm-roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3272
- Accuracy: 0.9087
- Precision: 0.8411
- Recall: 0.8441
- F1: 0.8426
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: 32
- eval_batch_size: 32
- seed: 42
- 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 | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 296 | 0.2705 | 0.9030 | 0.8368 | 0.8192 | 0.8276 |
| 0.3171 | 2.0 | 592 | 0.2174 | 0.9192 | 0.8847 | 0.8204 | 0.8476 |
| 0.3171 | 3.0 | 888 | 0.2250 | 0.9202 | 0.8658 | 0.8531 | 0.8593 |
| 0.2162 | 4.0 | 1184 | 0.2329 | 0.9106 | 0.8422 | 0.8538 | 0.8478 |
| 0.2162 | 5.0 | 1480 | 0.2260 | 0.9183 | 0.8584 | 0.8584 | 0.8584 |
| 0.1766 | 6.0 | 1776 | 0.2638 | 0.9116 | 0.8409 | 0.8651 | 0.8522 |
| 0.146 | 7.0 | 2072 | 0.3088 | 0.9125 | 0.8494 | 0.8464 | 0.8478 |
| 0.146 | 8.0 | 2368 | 0.2873 | 0.9154 | 0.8568 | 0.8459 | 0.8512 |
| 0.1166 | 9.0 | 2664 | 0.3227 | 0.9144 | 0.8518 | 0.8518 | 0.8518 |
| 0.1166 | 10.0 | 2960 | 0.3272 | 0.9087 | 0.8411 | 0.8441 | 0.8426 |
Framework versions
- Transformers 4.24.0.dev0
- Pytorch 1.11.0+cu102
- Datasets 2.6.1
- Tokenizers 0.13.1