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fc-binary-prompt-model

Transformers
PyTorch
distilbert
Generated from Trainer
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fc-binary-prompt-model

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  1. README.md +90 -0
  2. pytorch_model.bin +1 -1
README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: line-corporation/line-distilbert-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: fc-binary-prompt-model
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+ results: []
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+ ---
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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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+
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+ # fc-binary-prompt-model
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+
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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: 0.3462
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+ - Accuracy: 0.8652
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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: 64
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+ - eval_batch_size: 8
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+ - seed: 42
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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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+
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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 | 306 | 0.3968 | 0.8594 |
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+ | 0.425 | 2.0 | 612 | 0.3885 | 0.8594 |
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+ | 0.425 | 3.0 | 918 | 0.3809 | 0.8594 |
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+ | 0.4028 | 4.0 | 1224 | 0.3771 | 0.8594 |
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+ | 0.3962 | 5.0 | 1530 | 0.3717 | 0.8594 |
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+ | 0.3962 | 6.0 | 1836 | 0.3704 | 0.8594 |
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+ | 0.3919 | 7.0 | 2142 | 0.3708 | 0.8594 |
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+ | 0.3919 | 8.0 | 2448 | 0.3648 | 0.8594 |
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+ | 0.3897 | 9.0 | 2754 | 0.3759 | 0.8613 |
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+ | 0.3836 | 10.0 | 3060 | 0.3570 | 0.8594 |
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+ | 0.3836 | 11.0 | 3366 | 0.3643 | 0.8613 |
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+ | 0.3864 | 12.0 | 3672 | 0.3559 | 0.8613 |
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+ | 0.3864 | 13.0 | 3978 | 0.3557 | 0.8613 |
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+ | 0.3823 | 14.0 | 4284 | 0.3516 | 0.8613 |
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+ | 0.3808 | 15.0 | 4590 | 0.3580 | 0.8613 |
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+ | 0.3808 | 16.0 | 4896 | 0.3529 | 0.8613 |
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+ | 0.3759 | 17.0 | 5202 | 0.3498 | 0.8613 |
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+ | 0.3793 | 18.0 | 5508 | 0.3485 | 0.8613 |
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+ | 0.3793 | 19.0 | 5814 | 0.3495 | 0.8613 |
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+ | 0.3757 | 20.0 | 6120 | 0.3442 | 0.8613 |
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+ | 0.3757 | 21.0 | 6426 | 0.3481 | 0.8613 |
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+ | 0.3741 | 22.0 | 6732 | 0.3475 | 0.8633 |
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+ | 0.3775 | 23.0 | 7038 | 0.3478 | 0.8633 |
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+ | 0.3775 | 24.0 | 7344 | 0.3486 | 0.8633 |
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+ | 0.375 | 25.0 | 7650 | 0.3489 | 0.8652 |
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+ | 0.375 | 26.0 | 7956 | 0.3485 | 0.8652 |
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+ | 0.37 | 27.0 | 8262 | 0.3446 | 0.8613 |
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+ | 0.3712 | 28.0 | 8568 | 0.3463 | 0.8652 |
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+ | 0.3712 | 29.0 | 8874 | 0.3466 | 0.8652 |
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+ | 0.3748 | 30.0 | 9180 | 0.3462 | 0.8652 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.34.0
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+ - Pytorch 2.0.0+cu118
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+ - Datasets 2.14.5
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+ - Tokenizers 0.14.0
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