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--- |
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license: gpl-3.0 |
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base_model: ckiplab/bert-base-chinese |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: bert-base-chinese-finetuned-QA-b8 |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# bert-base-chinese-finetuned-QA-b8 |
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This model is a fine-tuned version of [ckiplab/bert-base-chinese](https://huggingface.co/ckiplab/bert-base-chinese) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.3405 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 3e-05 |
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- train_batch_size: 2 |
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- eval_batch_size: 2 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 8 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 4 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:-----:|:---------------:| |
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| 1.9325 | 0.14 | 500 | 1.2076 | |
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| 1.1199 | 0.29 | 1000 | 1.0315 | |
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| 1.0118 | 0.43 | 1500 | 0.9836 | |
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| 0.9398 | 0.58 | 2000 | 0.9762 | |
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| 0.9526 | 0.72 | 2500 | 0.9374 | |
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| 0.9142 | 0.87 | 3000 | 0.8783 | |
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| 0.8265 | 1.01 | 3500 | 0.9919 | |
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| 0.6091 | 1.16 | 4000 | 0.9613 | |
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| 0.6303 | 1.3 | 4500 | 0.9769 | |
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| 0.6161 | 1.45 | 5000 | 0.9882 | |
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| 0.6109 | 1.59 | 5500 | 0.9160 | |
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| 0.5887 | 1.73 | 6000 | 0.9105 | |
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| 0.5811 | 1.88 | 6500 | 0.9812 | |
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| 0.5638 | 2.02 | 7000 | 1.0669 | |
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| 0.4174 | 2.17 | 7500 | 1.2101 | |
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| 0.3958 | 2.31 | 8000 | 1.2186 | |
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| 0.4032 | 2.46 | 8500 | 1.1691 | |
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| 0.4183 | 2.6 | 9000 | 1.0890 | |
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| 0.4247 | 2.75 | 9500 | 1.0721 | |
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| 0.3917 | 2.89 | 10000 | 1.1714 | |
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| 0.3738 | 3.04 | 10500 | 1.1794 | |
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| 0.29 | 3.18 | 11000 | 1.2494 | |
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| 0.326 | 3.32 | 11500 | 1.2822 | |
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| 0.3076 | 3.47 | 12000 | 1.3214 | |
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| 0.3071 | 3.61 | 12500 | 1.2968 | |
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| 0.2797 | 3.76 | 13000 | 1.3410 | |
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| 0.3192 | 3.9 | 13500 | 1.3405 | |
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### Framework versions |
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- Transformers 4.34.0 |
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- Pytorch 1.13.1+cu116 |
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- Datasets 2.14.5 |
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- Tokenizers 0.14.1 |
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