xlm-roberta-large-mongolian-ner
This model is a fine-tuned version of xlm-roberta-large on the None dataset. It achieves the following results on the evaluation set:
- eval_loss: 0.0951
- eval_precision: 0.9279
- eval_recall: 0.9375
- eval_f1: 0.9327
- eval_accuracy: 0.9807
- eval_runtime: 90.3965
- eval_samples_per_second: 28.109
- eval_steps_per_second: 0.885
- epoch: 5.0
- step: 2385
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
Framework versions
- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
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