xlm-turkish-ner
This model is a fine-tuned version of xlm-roberta-large on the turkish_ner dataset. It achieves the following results on the evaluation set:
- Loss: 0.2836
- F1: 0.6578
- Precision: 0.6670
- Recall: 0.6489
- Accuracy: 0.9114
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: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- 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: 5
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | F1 | Precision | Recall | Accuracy |
---|---|---|---|---|---|---|---|
0.2704 | 1.0 | 1250 | 0.2745 | 0.6153 | 0.6250 | 0.6059 | 0.8985 |
0.2047 | 2.0 | 2500 | 0.2656 | 0.6372 | 0.6429 | 0.6315 | 0.9046 |
0.1646 | 3.0 | 3750 | 0.2628 | 0.6560 | 0.6839 | 0.6303 | 0.9109 |
0.1256 | 4.0 | 5000 | 0.2895 | 0.6561 | 0.6641 | 0.6482 | 0.9092 |
0.0953 | 5.0 | 6250 | 0.3224 | 0.6555 | 0.6554 | 0.6556 | 0.9088 |
Framework versions
- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0
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Base model
FacebookAI/xlm-roberta-largeDataset used to train meryemmm22/xlm-turkish-ner
Evaluation results
- F1 on turkish_nerself-reported0.658
- Precision on turkish_nerself-reported0.667
- Recall on turkish_nerself-reported0.649
- Accuracy on turkish_nerself-reported0.911