bert-base-cased-ner-jnlpba-strong-labelled
This model is a fine-tuned version of bert-base-cased on the None dataset. It achieves the following results on the evaluation set:
- eval_loss: 1.7948
- eval_accuracy: 0.1970
- eval_runtime: 49.3802
- eval_samples_per_second: 156.217
- eval_steps_per_second: 9.781
- step: 0
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: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
Framework versions
- Transformers 4.25.1
- Pytorch 1.12.1+cu113
- Datasets 2.8.0
- Tokenizers 0.13.2
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