metadata
base_model: bert-base-chinese
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: berttest2
results: []
berttest2
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: 0.0206
- Precision: 0.9610
- Recall: 0.9653
- F1: 0.9631
- Accuracy: 0.9956
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: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.028 | 1.0 | 2609 | 0.0225 | 0.9385 | 0.9350 | 0.9368 | 0.9932 |
| 0.011 | 2.0 | 5218 | 0.0182 | 0.9542 | 0.9592 | 0.9567 | 0.9951 |
| 0.0044 | 3.0 | 7827 | 0.0206 | 0.9610 | 0.9653 | 0.9631 | 0.9956 |
Framework versions
- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1