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--- |
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base_model: bert-base-chinese |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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model-index: |
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- name: BERT_test_graident_accumulation_test4 |
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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_test_graident_accumulation_test4 |
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This model is a fine-tuned version of [bert-base-chinese](https://huggingface.co/bert-base-chinese) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.1752 |
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- Accuracy: 0.5781 |
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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: 5e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 8 |
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- total_train_batch_size: 64 |
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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: 3 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| No log | 1.0 | 116 | 1.0083 | 0.5586 | |
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| No log | 1.99 | 232 | 1.0274 | 0.5913 | |
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| No log | 2.99 | 348 | 1.1752 | 0.5781 | |
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### Framework versions |
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- Transformers 4.36.0 |
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- Pytorch 2.1.1+cu118 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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