metadata
library_name: transformers
license: mit
base_model: xlm-roberta-large
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: x5-ner-with-augmentation-in-flight
results: []
x5-ner-with-augmentation-in-flight
This model is a fine-tuned version of xlm-roberta-large on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3224
- Precision: 0.9316
- Recall: 0.9553
- F1: 0.9433
- Accuracy: 0.9453
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
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Accuracy | F1 | Validation Loss | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.3995 | 1.0 | 3631 | 0.9135 | 0.8831 | 0.3011 | 0.8761 | 0.8903 |
| 0.3472 | 2.0 | 7262 | 0.9312 | 0.9173 | 0.2802 | 0.9080 | 0.9267 |
| 0.318 | 3.0 | 10893 | 0.9385 | 0.9325 | 0.2597 | 0.9174 | 0.9480 |
| 0.2956 | 4.0 | 14524 | 0.9401 | 0.9387 | 0.2870 | 0.9262 | 0.9515 |
| 0.2837 | 5.0 | 18155 | 0.9401 | 0.9374 | 0.2796 | 0.9271 | 0.9480 |
| 0.2601 | 6.0 | 21786 | 0.9423 | 0.9393 | 0.2723 | 0.9266 | 0.9524 |
| 0.2482 | 7.0 | 25417 | 0.9458 | 0.9464 | 0.2683 | 0.9361 | 0.9569 |
| 0.2364 | 8.0 | 29048 | 0.3210 | 0.9310 | 0.9550 | 0.9429 | 0.9432 |
| 0.2077 | 9.0 | 32679 | 0.3160 | 0.9349 | 0.9572 | 0.9459 | 0.9455 |
| 0.1616 | 10.0 | 36310 | 0.3224 | 0.9316 | 0.9553 | 0.9433 | 0.9453 |
Framework versions
- Transformers 4.53.3
- Pytorch 2.7.1+cu118
- Datasets 3.6.0
- Tokenizers 0.21.4