finetune-bert-base-multilingual-cased-ner-hrl

<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. -->

finetune-bert-base-multilingual-cased-ner-hrl

This model is a fine-tuned version of Davlan/bert-base-multilingual-cased-ner-hrl on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.0332
• Precision: 0.9543
• Recall: 0.9535
• F1: 0.9539
• Accuracy: 0.9554

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: 12
• eval_batch_size: 12
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_ratio: 0.3333333333333333
• num_epochs: 5
• mixed_precision_training: Native AMP

Training results

Framework versions

• Transformers 4.21.3
• Pytorch 1.10.1+cu113
• Datasets 2.4.0
• Tokenizers 0.12.1