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bert-base-chinese-SSEC
hw2942/bert-base-chinese-SSEC
bert-base-chinese-SSEC is a text classification model from hw2942. Use it when you need a label for a piece of text. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- bert
- Access
- Public
- Created
- Aug 14, 2023
- Updated
- Aug 14, 2023
- SHA
- e9c6cda6
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Base models
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-wallstreetcn-morning-news-market-overview-SSEC-v3
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: 3.1007
- Accuracy: 0.6875
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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 34 | 2.2173 | 0.7188 |
| No log | 2.0 | 68 | 1.8368 | 0.7188 |
| No log | 3.0 | 102 | 2.7822 | 0.625 |
| No log | 4.0 | 136 | 2.3597 | 0.7188 |
| No log | 5.0 | 170 | 3.3032 | 0.5312 |
| No log | 6.0 | 204 | 2.9527 | 0.6562 |
| No log | 7.0 | 238 | 2.7575 | 0.6875 |
| No log | 8.0 | 272 | 2.9714 | 0.6875 |
| No log | 9.0 | 306 | 3.0941 | 0.6875 |
| No log | 10.0 | 340 | 3.1007 | 0.6875 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- Created
- Aug 14, 2023
- Updated
- Aug 14, 2023