metadata
library_name: transformers
base_model: bert-base-chinese
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: ecom_ner_model
results: []
ecom_ner_model
This model is a fine-tuned version of bert-base-chinese on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3748
- Precision: 0.7042
- Recall: 0.8002
- F1: 0.7491
- Accuracy: 0.8704
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: 96
- eval_batch_size: 96
- seed: 42
- optimizer: Use OptimizerNames.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: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 63 | 0.4615 | 0.6520 | 0.7503 | 0.6977 | 0.8442 |
| No log | 2.0 | 126 | 0.3863 | 0.7008 | 0.7913 | 0.7433 | 0.8668 |
| No log | 3.0 | 189 | 0.3748 | 0.7042 | 0.8002 | 0.7491 | 0.8704 |
Framework versions
- Transformers 4.49.0
- Pytorch 2.6.0+cu124
- Tokenizers 0.21.1