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bert-finetuned-weibo-luobokuaipao

Text Classification
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bert
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text-embeddings-inference
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End of training

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  1. README.md +14 -7
  2. runs/Jul26_02-59-35_ac64ee777514/events.out.tfevents.1721962786.ac64ee777514.267.0 +2 -2
README.md CHANGED
@@ -16,8 +16,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [bert-base-chinese](https://huggingface.co/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: 1.1877
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- - Accuracy: 0.6322
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  ## Model description
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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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  - 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: 3.0
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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 | 198 | 1.0607 | 0.5995 |
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- | No log | 2.0 | 396 | 0.9555 | 0.6448 |
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- | 0.6334 | 3.0 | 594 | 1.1877 | 0.6322 |
 
 
 
 
 
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [bert-base-chinese](https://huggingface.co/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: 1.0773
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+ - Accuracy: 0.4358
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 0.0001
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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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  - 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: 10
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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 | 198 | 1.1293 | 0.2846 |
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+ | No log | 2.0 | 396 | 1.0949 | 0.4332 |
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+ | 1.0985 | 3.0 | 594 | 1.0794 | 0.4332 |
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+ | 1.0985 | 4.0 | 792 | 1.0780 | 0.4332 |
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+ | 1.0985 | 5.0 | 990 | 1.0810 | 0.4332 |
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+ | 1.0852 | 6.0 | 1188 | 1.0637 | 0.4610 |
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+ | 1.0852 | 7.0 | 1386 | 1.0851 | 0.4332 |
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+ | 1.0777 | 8.0 | 1584 | 1.0832 | 0.4358 |
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+ | 1.0777 | 9.0 | 1782 | 1.0817 | 0.4358 |
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+ | 1.0777 | 10.0 | 1980 | 1.0773 | 0.4358 |
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  ### Framework versions
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