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bert-base-chinese-finetuned-qqp-FHTMMT-5x-CKIPtokenizer
r10521708/bert-base-chinese-finetuned-qqp-FHTMMT-5x-CKIPtokenizer
bert-base-chinese-finetuned-qqp-FHTMMT-5x-CKIPtokenizer is a text classification model from r10521708. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as gpl-3.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- gpl-3.0
- Model type
- bert
- Access
- Public
- Created
- Jun 14, 2023
- Updated
- Jun 14, 2023
- SHA
- 9f018343
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Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
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
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- License
- gpl-3.0
- Created
- Jun 14, 2023
- Updated
- Jun 14, 2023