bert-base-chinese-finetuned-qqp-FHTMMT-5x-CKIPtokenizer
This model is a fine-tuned version of ckiplab/bert-base-chinese on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1249
- Accuracy: 0.965
- F1: 0.9659
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: 5
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
---|---|---|---|---|---|
No log | 1.0 | 93 | 0.2657 | 0.925 | 0.9239 |
No log | 2.0 | 186 | 0.1909 | 0.935 | 0.9340 |
No log | 3.0 | 279 | 0.1651 | 0.96 | 0.9608 |
No log | 4.0 | 372 | 0.1446 | 0.955 | 0.9561 |
No log | 5.0 | 465 | 0.1249 | 0.965 | 0.9659 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1
- Datasets 2.9.0
- Tokenizers 0.13.0.dev0
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