<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. -->
mn-xlm-roberta-base-named-entity
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: 0.1224
- Precision: 0.9275
- Recall: 0.9364
- F1: 0.9319
- Accuracy: 0.9783
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: 16
- 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 | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.2015 | 1.0 | 477 | 0.0915 | 0.8830 | 0.9076 | 0.8951 | 0.9724 |
| 0.0837 | 2.0 | 954 | 0.0872 | 0.9089 | 0.9202 | 0.9145 | 0.9757 |
| 0.0605 | 3.0 | 1431 | 0.0814 | 0.9134 | 0.9275 | 0.9204 | 0.9768 |
| 0.0447 | 4.0 | 1908 | 0.0906 | 0.9219 | 0.9316 | 0.9267 | 0.9774 |
| 0.0317 | 5.0 | 2385 | 0.0969 | 0.9229 | 0.9330 | 0.9280 | 0.9782 |
| 0.0254 | 6.0 | 2862 | 0.1121 | 0.9216 | 0.9343 | 0.9279 | 0.9777 |
| 0.0195 | 7.0 | 3339 | 0.1143 | 0.9298 | 0.9364 | 0.9331 | 0.9790 |
| 0.0145 | 8.0 | 3816 | 0.1175 | 0.9229 | 0.9337 | 0.9283 | 0.9773 |
| 0.0114 | 9.0 | 4293 | 0.1205 | 0.9233 | 0.9332 | 0.9282 | 0.9774 |
| 0.0091 | 10.0 | 4770 | 0.1224 | 0.9275 | 0.9364 | 0.9319 | 0.9783 |
Framework versions
- Transformers 4.28.0
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
