bert-base-cased-conversational-ner

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bert-base-cased-conversational-ner

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

• Loss: 0.3583
• Job Title precision: 0.8377
• Job Title recall: 0.8317
• Job Title f1: 0.8347
• Loc precision: 0.8938
• Loc recall: 0.9340
• Loc f1: 0.9135
• Org precision: 0.7092
• Org recall: 0.7032
• Org f1: 0.7062
• Misc precision: 0.6246
• Misc recall: 0.7270
• Misc f1: 0.6719
• Precision: 0.8154
• Recall: 0.8240
• F1: 0.8197
• Accuracy: 0.8687

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: 8
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 10

Training results

Framework versions

• Transformers 4.28.1
• Pytorch 1.7.1+cu110
• Datasets 2.12.0
• Tokenizers 0.13.2