bert-base-multilingual-cased-finetuned-conllpp

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bert-base-multilingual-cased-finetuned-conllpp

This model is a fine-tuned version of bert-base-multilingual-cased on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.0443
• Accuracy: 0.9850
• Precision: 0.9304
• Recall: 0.9357
• F1: 0.9330

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: 1e-05
• train_batch_size: 8
• eval_batch_size: 8
• seed: 1
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_ratio: 0.05
• num_epochs: 3

Training results

Framework versions

• Transformers 4.43.4
• Pytorch 2.4.1+cu121
• Datasets 3.0.1
• Tokenizers 0.19.1