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bert-base-chinese
watsonpro/bert-base-chinese
bert-base-chinese is a text classification model from watsonpro. 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
- albert
- Access
- Public
- Created
- Jan 20, 2024
- Updated
- Jan 20, 2024
- SHA
- af812379
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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
This model is a fine-tuned version of ckiplab/albert-base-chinese on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6943
- F1: 0.5455
- Roc Auc: 0.5500
- Accuracy: 0.0
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: 128
- eval_batch_size: 128
- 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 | F1 | Roc Auc | Accuracy |
|---|---|---|---|---|---|---|
| No log | 1.0 | 1 | 0.6943 | 0.5455 | 0.5500 | 0.0 |
| No log | 2.0 | 2 | 0.6945 | 0.5455 | 0.5500 | 0.0 |
| No log | 3.0 | 3 | 0.6947 | 0.5455 | 0.5500 | 0.0 |
| No log | 4.0 | 4 | 0.6949 | 0.5455 | 0.5500 | 0.0 |
| No log | 5.0 | 5 | 0.6949 | 0.5455 | 0.5500 | 0.0 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
- Task
- Text Classification
- Library
- transformers
- Type
- albert
- License
- gpl-3.0
- Created
- Jan 20, 2024
- Updated
- Jan 20, 2024