bert_crf-ner-weibo
This model is a fine-tuned version of google-bert/bert-base-chinese on an unknown dataset. It achieves the following results on the evaluation set:
- eval_loss: 0.2287
- eval_precision: 0.6344
- eval_recall: 0.7584
- eval_f1: 0.6909
- eval_accuracy: 0.9678
- eval_runtime: 0.5124
- eval_samples_per_second: 524.958
- eval_steps_per_second: 9.758
- epoch: 115.0
- step: 2530
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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 200
- mixed_precision_training: Native AMP
Framework versions
- Transformers 4.46.1
- Pytorch 1.13.1+cu117
- Datasets 3.1.0
- Tokenizers 0.20.2
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Model tree for PassbyGrocer/bert_crf-ner-weibo
Base model
google-bert/bert-base-chinese