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distilbert
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  2. pytorch_model.bin +1 -1
README.md CHANGED
@@ -17,8 +17,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [line-corporation/line-distilbert-base-japanese](https://huggingface.co/line-corporation/line-distilbert-base-japanese) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.3796
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- - Accuracy: 0.9258
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  ## Model description
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@@ -44,18 +44,42 @@ The following hyperparameters were used during training:
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  - distributed_type: tpu
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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: 6
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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 | 306 | 0.2649 | 0.9160 |
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- | 0.2942 | 2.0 | 612 | 0.2373 | 0.9082 |
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- | 0.2942 | 3.0 | 918 | 0.2091 | 0.9219 |
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- | 0.1394 | 4.0 | 1224 | 0.2558 | 0.9355 |
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- | 0.0607 | 5.0 | 1530 | 0.2584 | 0.9238 |
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- | 0.0607 | 6.0 | 1836 | 0.3796 | 0.9258 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [line-corporation/line-distilbert-base-japanese](https://huggingface.co/line-corporation/line-distilbert-base-japanese) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.3471
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+ - Accuracy: 0.8672
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  ## Model description
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  - distributed_type: tpu
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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: 30
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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 | 306 | 0.3968 | 0.8594 |
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+ | 0.4221 | 2.0 | 612 | 0.3889 | 0.8594 |
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+ | 0.4221 | 3.0 | 918 | 0.3814 | 0.8594 |
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+ | 0.4026 | 4.0 | 1224 | 0.3775 | 0.8594 |
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+ | 0.396 | 5.0 | 1530 | 0.3724 | 0.8594 |
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+ | 0.396 | 6.0 | 1836 | 0.3707 | 0.8594 |
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+ | 0.392 | 7.0 | 2142 | 0.3721 | 0.8594 |
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+ | 0.392 | 8.0 | 2448 | 0.3653 | 0.8594 |
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+ | 0.3898 | 9.0 | 2754 | 0.3765 | 0.8613 |
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+ | 0.3835 | 10.0 | 3060 | 0.3572 | 0.8594 |
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+ | 0.3835 | 11.0 | 3366 | 0.3664 | 0.8613 |
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+ | 0.3869 | 12.0 | 3672 | 0.3568 | 0.8613 |
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+ | 0.3869 | 13.0 | 3978 | 0.3583 | 0.8613 |
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+ | 0.3825 | 14.0 | 4284 | 0.3526 | 0.8613 |
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+ | 0.3813 | 15.0 | 4590 | 0.3581 | 0.8613 |
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+ | 0.3813 | 16.0 | 4896 | 0.3553 | 0.8613 |
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+ | 0.3759 | 17.0 | 5202 | 0.3504 | 0.8613 |
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+ | 0.3788 | 18.0 | 5508 | 0.3490 | 0.8613 |
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+ | 0.3788 | 19.0 | 5814 | 0.3520 | 0.8613 |
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+ | 0.3754 | 20.0 | 6120 | 0.3450 | 0.8613 |
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+ | 0.3754 | 21.0 | 6426 | 0.3494 | 0.8633 |
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+ | 0.3748 | 22.0 | 6732 | 0.3491 | 0.8633 |
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+ | 0.3775 | 23.0 | 7038 | 0.3499 | 0.8633 |
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+ | 0.3775 | 24.0 | 7344 | 0.3494 | 0.8633 |
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+ | 0.3748 | 25.0 | 7650 | 0.3504 | 0.8672 |
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+ | 0.3748 | 26.0 | 7956 | 0.3495 | 0.8672 |
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+ | 0.3701 | 27.0 | 8262 | 0.3454 | 0.8633 |
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+ | 0.3712 | 28.0 | 8568 | 0.3472 | 0.8633 |
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+ | 0.3712 | 29.0 | 8874 | 0.3478 | 0.8672 |
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+ | 0.3751 | 30.0 | 9180 | 0.3471 | 0.8672 |
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  ### Framework versions
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