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