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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: factual-consistency-classification-with-prompt-ja |
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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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# factual-consistency-classification-with-prompt-ja |
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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: 0.6642 |
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- Accuracy: 0.6738 |
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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: 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: 100 |
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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 | 1.0023 | 0.3223 | |
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| 1.0128 | 2.0 | 612 | 0.9182 | 0.5742 | |
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| 1.0128 | 3.0 | 918 | 0.8847 | 0.5547 | |
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| 0.9226 | 4.0 | 1224 | 0.8569 | 0.5859 | |
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| 0.8815 | 5.0 | 1530 | 0.8329 | 0.6191 | |
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| 0.8815 | 6.0 | 1836 | 0.8287 | 0.5840 | |
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| 0.8633 | 7.0 | 2142 | 0.8160 | 0.5723 | |
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| 0.8633 | 8.0 | 2448 | 0.8210 | 0.5098 | |
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| 0.8525 | 9.0 | 2754 | 0.8171 | 0.5156 | |
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| 0.8418 | 10.0 | 3060 | 0.7850 | 0.5840 | |
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| 0.8418 | 11.0 | 3366 | 0.7771 | 0.6035 | |
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| 0.8323 | 12.0 | 3672 | 0.7652 | 0.6797 | |
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| 0.8323 | 13.0 | 3978 | 0.7655 | 0.6055 | |
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| 0.8292 | 14.0 | 4284 | 0.7556 | 0.6719 | |
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| 0.8233 | 15.0 | 4590 | 0.7578 | 0.6660 | |
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| 0.8233 | 16.0 | 4896 | 0.7497 | 0.6270 | |
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| 0.8173 | 17.0 | 5202 | 0.7472 | 0.6484 | |
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| 0.8122 | 18.0 | 5508 | 0.7334 | 0.7090 | |
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| 0.8122 | 19.0 | 5814 | 0.7468 | 0.6016 | |
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| 0.8165 | 20.0 | 6120 | 0.7248 | 0.7363 | |
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| 0.8165 | 21.0 | 6426 | 0.7324 | 0.6484 | |
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| 0.8048 | 22.0 | 6732 | 0.7261 | 0.6836 | |
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| 0.8033 | 23.0 | 7038 | 0.7187 | 0.7031 | |
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| 0.8033 | 24.0 | 7344 | 0.7205 | 0.6816 | |
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| 0.8011 | 25.0 | 7650 | 0.7307 | 0.6133 | |
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| 0.8011 | 26.0 | 7956 | 0.7220 | 0.6680 | |
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| 0.7979 | 27.0 | 8262 | 0.7175 | 0.6660 | |
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| 0.7963 | 28.0 | 8568 | 0.7205 | 0.6367 | |
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| 0.7963 | 29.0 | 8874 | 0.7139 | 0.6719 | |
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| 0.7942 | 30.0 | 9180 | 0.7078 | 0.6875 | |
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| 0.7942 | 31.0 | 9486 | 0.7094 | 0.6602 | |
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| 0.7878 | 32.0 | 9792 | 0.6992 | 0.7148 | |
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| 0.7891 | 33.0 | 10098 | 0.7041 | 0.6680 | |
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| 0.7891 | 34.0 | 10404 | 0.6968 | 0.6973 | |
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| 0.7869 | 35.0 | 10710 | 0.7047 | 0.6465 | |
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| 0.7874 | 36.0 | 11016 | 0.6962 | 0.6934 | |
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| 0.7874 | 37.0 | 11322 | 0.7026 | 0.6523 | |
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| 0.7817 | 38.0 | 11628 | 0.7103 | 0.625 | |
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| 0.7817 | 39.0 | 11934 | 0.6917 | 0.6914 | |
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| 0.7843 | 40.0 | 12240 | 0.6957 | 0.6680 | |
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| 0.7805 | 41.0 | 12546 | 0.7016 | 0.6484 | |
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| 0.7805 | 42.0 | 12852 | 0.6955 | 0.6582 | |
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| 0.7777 | 43.0 | 13158 | 0.7004 | 0.6387 | |
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| 0.7777 | 44.0 | 13464 | 0.6855 | 0.6895 | |
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| 0.7783 | 45.0 | 13770 | 0.6835 | 0.6895 | |
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| 0.7766 | 46.0 | 14076 | 0.6886 | 0.6641 | |
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| 0.7766 | 47.0 | 14382 | 0.6969 | 0.6309 | |
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| 0.7796 | 48.0 | 14688 | 0.6873 | 0.6738 | |
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| 0.7796 | 49.0 | 14994 | 0.6796 | 0.6953 | |
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| 0.77 | 50.0 | 15300 | 0.6908 | 0.6543 | |
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| 0.7768 | 51.0 | 15606 | 0.6900 | 0.6367 | |
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| 0.7768 | 52.0 | 15912 | 0.6855 | 0.6680 | |
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| 0.7698 | 53.0 | 16218 | 0.6905 | 0.6504 | |
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| 0.7686 | 54.0 | 16524 | 0.6783 | 0.6816 | |
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| 0.7686 | 55.0 | 16830 | 0.6807 | 0.6777 | |
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| 0.7712 | 56.0 | 17136 | 0.6767 | 0.6797 | |
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| 0.7712 | 57.0 | 17442 | 0.6966 | 0.6152 | |
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| 0.7692 | 58.0 | 17748 | 0.6812 | 0.6660 | |
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| 0.7677 | 59.0 | 18054 | 0.6762 | 0.6777 | |
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| 0.7677 | 60.0 | 18360 | 0.6697 | 0.7090 | |
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| 0.761 | 61.0 | 18666 | 0.6833 | 0.6445 | |
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| 0.761 | 62.0 | 18972 | 0.6753 | 0.6777 | |
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| 0.7676 | 63.0 | 19278 | 0.6757 | 0.6699 | |
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| 0.7627 | 64.0 | 19584 | 0.6874 | 0.6426 | |
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| 0.7627 | 65.0 | 19890 | 0.6704 | 0.6836 | |
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| 0.7672 | 66.0 | 20196 | 0.6685 | 0.6934 | |
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| 0.7638 | 67.0 | 20502 | 0.6645 | 0.7090 | |
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| 0.7638 | 68.0 | 20808 | 0.6718 | 0.6797 | |
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| 0.765 | 69.0 | 21114 | 0.6658 | 0.6934 | |
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| 0.765 | 70.0 | 21420 | 0.6670 | 0.6895 | |
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| 0.7593 | 71.0 | 21726 | 0.6735 | 0.6719 | |
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| 0.7634 | 72.0 | 22032 | 0.6765 | 0.6406 | |
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| 0.7634 | 73.0 | 22338 | 0.6722 | 0.6641 | |
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| 0.754 | 74.0 | 22644 | 0.6664 | 0.6855 | |
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| 0.754 | 75.0 | 22950 | 0.6659 | 0.6895 | |
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| 0.7619 | 76.0 | 23256 | 0.6700 | 0.6621 | |
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| 0.7583 | 77.0 | 23562 | 0.6664 | 0.6797 | |
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| 0.7583 | 78.0 | 23868 | 0.6650 | 0.6836 | |
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| 0.7556 | 79.0 | 24174 | 0.6615 | 0.6973 | |
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| 0.7556 | 80.0 | 24480 | 0.6625 | 0.6934 | |
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| 0.7571 | 81.0 | 24786 | 0.6704 | 0.6582 | |
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| 0.7549 | 82.0 | 25092 | 0.6677 | 0.6719 | |
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| 0.7549 | 83.0 | 25398 | 0.6670 | 0.6699 | |
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| 0.7542 | 84.0 | 25704 | 0.6617 | 0.6875 | |
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| 0.756 | 85.0 | 26010 | 0.6638 | 0.6758 | |
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| 0.756 | 86.0 | 26316 | 0.6697 | 0.6562 | |
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| 0.7513 | 87.0 | 26622 | 0.6647 | 0.6738 | |
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| 0.7513 | 88.0 | 26928 | 0.6734 | 0.6445 | |
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| 0.7548 | 89.0 | 27234 | 0.6637 | 0.6836 | |
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| 0.7565 | 90.0 | 27540 | 0.6665 | 0.6719 | |
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| 0.7565 | 91.0 | 27846 | 0.6708 | 0.6504 | |
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| 0.7488 | 92.0 | 28152 | 0.6603 | 0.6895 | |
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| 0.7488 | 93.0 | 28458 | 0.6671 | 0.6582 | |
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| 0.7545 | 94.0 | 28764 | 0.6655 | 0.6699 | |
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| 0.7509 | 95.0 | 29070 | 0.6636 | 0.6777 | |
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| 0.7509 | 96.0 | 29376 | 0.6620 | 0.6816 | |
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| 0.7546 | 97.0 | 29682 | 0.6653 | 0.6719 | |
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| 0.7546 | 98.0 | 29988 | 0.6636 | 0.6738 | |
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| 0.7521 | 99.0 | 30294 | 0.6636 | 0.6758 | |
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| 0.755 | 100.0 | 30600 | 0.6642 | 0.6738 | |
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### Framework versions |
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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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