xlmr_finetuned_ner_600
This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0724
- Precision: 0.6876
- Recall: 0.7559
- F1: 0.7201
- Accuracy: 0.9769
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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|
| 0.0945 | 1.0 | 120 | 0.0678 | 0.6698 | 0.7752 | 0.7187 | 0.9776 |
| 0.0656 | 2.0 | 240 | 0.0700 | 0.6687 | 0.7683 | 0.7150 | 0.9773 |
| 0.0584 | 3.0 | 360 | 0.0724 | 0.6876 | 0.7559 | 0.7201 | 0.9769 |
| 0.0322 | 4.0 | 480 | 0.0750 | 0.6785 | 0.7628 | 0.7182 | 0.9771 |
Framework versions
- Transformers 4.57.1
- Pytorch 2.9.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1
