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ckiplab-albert-base-chinese-david-ner
This model is a fine-tuned version of ckiplab/albert-base-chinese on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2725
- Precision: 0.7354
- Recall: 0.7379
- F1: 0.7367
- Accuracy: 0.9278
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
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.4221 | 1.4 | 500 | 0.2888 | 0.7072 | 0.7414 | 0.7239 | 0.9169 |
| 0.1314 | 2.8 | 1000 | 0.2725 | 0.7354 | 0.7379 | 0.7367 | 0.9278 |
Framework versions
- Transformers 4.29.0.dev0
- Pytorch 1.10.1+cu113
- Datasets 2.11.0
- Tokenizers 0.13.3
