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bert-base-japanese-ghost_rate

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End of training

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  1. README.md +24 -10
  2. model.safetensors +1 -1
README.md CHANGED
@@ -3,6 +3,8 @@ license: cc-by-sa-4.0
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  base_model: cl-tohoku/bert-base-japanese
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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-japanese-ghost_rate
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  results: []
@@ -15,12 +17,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [cl-tohoku/bert-base-japanese](https://huggingface.co/cl-tohoku/bert-base-japanese) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - eval_loss: 1.9334
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- - eval_accuracy: 0.2259
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- - eval_runtime: 24.3951
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- - eval_samples_per_second: 31.933
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- - eval_steps_per_second: 2.009
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- - step: 0
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 2e-07
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- - train_batch_size: 16
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- - eval_batch_size: 16
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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: 15
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
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  base_model: cl-tohoku/bert-base-japanese
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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-base-japanese-ghost_rate
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  results: []
 
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  This model is a fine-tuned version of [cl-tohoku/bert-base-japanese](https://huggingface.co/cl-tohoku/bert-base-japanese) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.7155
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+ - Accuracy: 0.1667
 
 
 
 
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 2e-07
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+ - train_batch_size: 32
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+ - eval_batch_size: 32
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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: cosine
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+ - num_epochs: 10
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | No log | 1.0 | 275 | 1.7696 | 0.1858 |
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+ | 1.7385 | 2.0 | 550 | 1.7574 | 0.1821 |
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+ | 1.7385 | 3.0 | 825 | 1.7461 | 0.1785 |
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+ | 1.7262 | 4.0 | 1100 | 1.7364 | 0.1758 |
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+ | 1.7262 | 5.0 | 1375 | 1.7280 | 0.1712 |
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+ | 1.7105 | 6.0 | 1650 | 1.7221 | 0.1703 |
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+ | 1.7105 | 7.0 | 1925 | 1.7183 | 0.1667 |
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+ | 1.6983 | 8.0 | 2200 | 1.7163 | 0.1667 |
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+ | 1.6983 | 9.0 | 2475 | 1.7156 | 0.1667 |
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+ | 1.697 | 10.0 | 2750 | 1.7155 | 0.1667 |
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+
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  ### Framework versions
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