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bart-base-chinese-SSEC
hw2942/bart-base-chinese-SSEC
bart-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
- bart
- Access
- Public
- Created
- Aug 16, 2023
- Updated
- Aug 16, 2023
- SHA
- 906aa06f
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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. -->
bart-base-chinese-wallstreetcn-morning-news-market-overview-SSEC-v1
This model is a fine-tuned version of fnlp/bart-base-chinese on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.2056
- 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 | 68 | 0.6914 | 0.5625 |
| No log | 2.0 | 136 | 0.6649 | 0.5938 |
| No log | 3.0 | 204 | 0.7056 | 0.5938 |
| No log | 4.0 | 272 | 0.6510 | 0.6562 |
| No log | 5.0 | 340 | 1.1325 | 0.6875 |
| No log | 6.0 | 408 | 1.6671 | 0.6875 |
| No log | 7.0 | 476 | 2.0104 | 0.6875 |
| 0.4905 | 8.0 | 544 | 1.9887 | 0.6875 |
| 0.4905 | 9.0 | 612 | 2.2172 | 0.6875 |
| 0.4905 | 10.0 | 680 | 2.2056 | 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
- bart
- Created
- Aug 16, 2023
- Updated
- Aug 16, 2023