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--- |
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license: apache-2.0 |
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base_model: tohoku-nlp/bert-base-japanese-v3 |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: base-japanese-product-classification |
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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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# base-japanese-product-classification |
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This model is a fine-tuned version of [tohoku-nlp/bert-base-japanese-v3](https://huggingface.co/tohoku-nlp/bert-base-japanese-v3) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.9961 |
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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: 2e-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: 100 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:-----:|:---------------:| |
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| No log | 1.0 | 106 | 3.5780 | |
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| No log | 2.0 | 212 | 2.6684 | |
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| No log | 3.0 | 318 | 2.1910 | |
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| No log | 4.0 | 424 | 1.8626 | |
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| 2.5157 | 5.0 | 530 | 1.6483 | |
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| 2.5157 | 6.0 | 636 | 1.4929 | |
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| 2.5157 | 7.0 | 742 | 1.3580 | |
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| 2.5157 | 8.0 | 848 | 1.2658 | |
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| 2.5157 | 9.0 | 954 | 1.1877 | |
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| 0.9057 | 10.0 | 1060 | 1.1381 | |
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| 0.9057 | 11.0 | 1166 | 1.0945 | |
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| 0.9057 | 12.0 | 1272 | 1.0589 | |
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| 0.9057 | 13.0 | 1378 | 1.0071 | |
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| 0.9057 | 14.0 | 1484 | 1.0002 | |
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| 0.4676 | 15.0 | 1590 | 0.9647 | |
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| 0.4676 | 16.0 | 1696 | 0.9762 | |
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| 0.4676 | 17.0 | 1802 | 0.9129 | |
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| 0.4676 | 18.0 | 1908 | 0.9316 | |
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| 0.2485 | 19.0 | 2014 | 0.9119 | |
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| 0.2485 | 20.0 | 2120 | 0.8805 | |
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| 0.2485 | 21.0 | 2226 | 0.8808 | |
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| 0.2485 | 22.0 | 2332 | 0.8769 | |
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| 0.2485 | 23.0 | 2438 | 0.8701 | |
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| 0.1331 | 24.0 | 2544 | 0.8651 | |
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| 0.1331 | 25.0 | 2650 | 0.8621 | |
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| 0.1331 | 26.0 | 2756 | 0.8759 | |
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| 0.1331 | 27.0 | 2862 | 0.8702 | |
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| 0.1331 | 28.0 | 2968 | 0.8634 | |
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| 0.0748 | 29.0 | 3074 | 0.8778 | |
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| 0.0748 | 30.0 | 3180 | 0.8776 | |
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| 0.0748 | 31.0 | 3286 | 0.8486 | |
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| 0.0748 | 32.0 | 3392 | 0.8695 | |
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| 0.0748 | 33.0 | 3498 | 0.8479 | |
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| 0.0416 | 34.0 | 3604 | 0.8661 | |
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| 0.0416 | 35.0 | 3710 | 0.8731 | |
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| 0.0416 | 36.0 | 3816 | 0.8681 | |
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| 0.0416 | 37.0 | 3922 | 0.8942 | |
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| 0.0255 | 38.0 | 4028 | 0.8841 | |
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| 0.0255 | 39.0 | 4134 | 0.8842 | |
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| 0.0255 | 40.0 | 4240 | 0.8875 | |
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| 0.0255 | 41.0 | 4346 | 0.8760 | |
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| 0.0255 | 42.0 | 4452 | 0.8820 | |
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| 0.0166 | 43.0 | 4558 | 0.8975 | |
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| 0.0166 | 44.0 | 4664 | 0.8890 | |
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| 0.0166 | 45.0 | 4770 | 0.8795 | |
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| 0.0166 | 46.0 | 4876 | 0.8882 | |
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| 0.0166 | 47.0 | 4982 | 0.8950 | |
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| 0.0123 | 48.0 | 5088 | 0.8923 | |
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| 0.0123 | 49.0 | 5194 | 0.9018 | |
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| 0.0123 | 50.0 | 5300 | 0.8975 | |
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| 0.0123 | 51.0 | 5406 | 0.9078 | |
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| 0.0097 | 52.0 | 5512 | 0.9124 | |
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| 0.0097 | 53.0 | 5618 | 0.9250 | |
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| 0.0097 | 54.0 | 5724 | 0.9663 | |
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| 0.0097 | 55.0 | 5830 | 0.9651 | |
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| 0.0097 | 56.0 | 5936 | 0.9570 | |
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| 0.0078 | 57.0 | 6042 | 0.9530 | |
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| 0.0078 | 58.0 | 6148 | 0.9548 | |
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| 0.0078 | 59.0 | 6254 | 0.9490 | |
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| 0.0078 | 60.0 | 6360 | 0.9563 | |
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| 0.0078 | 61.0 | 6466 | 0.9614 | |
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| 0.0064 | 62.0 | 6572 | 0.9602 | |
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| 0.0064 | 63.0 | 6678 | 0.9614 | |
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| 0.0064 | 64.0 | 6784 | 0.9625 | |
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| 0.0064 | 65.0 | 6890 | 0.9587 | |
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| 0.0064 | 66.0 | 6996 | 0.9601 | |
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| 0.0055 | 67.0 | 7102 | 0.9664 | |
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| 0.0055 | 68.0 | 7208 | 0.9688 | |
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| 0.0055 | 69.0 | 7314 | 0.9725 | |
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| 0.0055 | 70.0 | 7420 | 0.9726 | |
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| 0.0047 | 71.0 | 7526 | 0.9693 | |
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| 0.0047 | 72.0 | 7632 | 0.9737 | |
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| 0.0047 | 73.0 | 7738 | 0.9720 | |
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| 0.0047 | 74.0 | 7844 | 0.9717 | |
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| 0.0047 | 75.0 | 7950 | 0.9683 | |
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| 0.0041 | 76.0 | 8056 | 0.9732 | |
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| 0.0041 | 77.0 | 8162 | 0.9740 | |
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| 0.0041 | 78.0 | 8268 | 0.9748 | |
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| 0.0041 | 79.0 | 8374 | 0.9789 | |
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| 0.0041 | 80.0 | 8480 | 0.9788 | |
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| 0.0036 | 81.0 | 8586 | 0.9788 | |
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| 0.0036 | 82.0 | 8692 | 0.9829 | |
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| 0.0036 | 83.0 | 8798 | 0.9842 | |
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| 0.0036 | 84.0 | 8904 | 0.9810 | |
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| 0.0032 | 85.0 | 9010 | 0.9862 | |
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| 0.0032 | 86.0 | 9116 | 0.9858 | |
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| 0.0032 | 87.0 | 9222 | 0.9881 | |
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| 0.0032 | 88.0 | 9328 | 0.9889 | |
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| 0.0032 | 89.0 | 9434 | 0.9902 | |
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| 0.003 | 90.0 | 9540 | 0.9909 | |
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| 0.003 | 91.0 | 9646 | 0.9927 | |
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| 0.003 | 92.0 | 9752 | 0.9926 | |
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| 0.003 | 93.0 | 9858 | 0.9942 | |
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| 0.003 | 94.0 | 9964 | 0.9949 | |
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| 0.0028 | 95.0 | 10070 | 0.9926 | |
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| 0.0028 | 96.0 | 10176 | 0.9938 | |
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| 0.0028 | 97.0 | 10282 | 0.9949 | |
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| 0.0028 | 98.0 | 10388 | 0.9960 | |
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| 0.0028 | 99.0 | 10494 | 0.9960 | |
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| 0.0027 | 100.0 | 10600 | 0.9961 | |
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### Framework versions |
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- Transformers 4.39.1 |
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- Pytorch 2.2.0+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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