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--- |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: myBit-Llama2-jp-127M-3 |
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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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# myBit-Llama2-jp-127M-3 |
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This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 13.0221 |
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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: 0.001 |
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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: polynomial |
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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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| 7.8184 | 1.25 | 10 | 8.3355 | |
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| 5.4327 | 2.5 | 20 | 7.6000 | |
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| 5.0861 | 3.75 | 30 | 7.8126 | |
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| 4.7586 | 5.0 | 40 | 7.5748 | |
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| 4.4392 | 6.25 | 50 | 7.4509 | |
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| 4.1938 | 7.5 | 60 | 7.3834 | |
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| 4.0095 | 8.75 | 70 | 7.2750 | |
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| 3.905 | 10.0 | 80 | 7.3800 | |
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| 3.6536 | 11.25 | 90 | 7.4560 | |
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| 3.3187 | 12.5 | 100 | 7.6310 | |
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| 3.3315 | 13.75 | 110 | 8.0397 | |
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| 2.9308 | 15.0 | 120 | 8.3902 | |
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| 2.679 | 16.25 | 130 | 9.0364 | |
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| 2.2896 | 17.5 | 140 | 9.8766 | |
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| 1.8407 | 18.75 | 150 | 10.7682 | |
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| 1.5081 | 20.0 | 160 | 11.7175 | |
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| 0.9778 | 21.25 | 170 | 12.8239 | |
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| 0.6572 | 22.5 | 180 | 13.6506 | |
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| 0.5411 | 23.75 | 190 | 14.2579 | |
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| 0.44 | 25.0 | 200 | 14.5732 | |
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| 0.3283 | 26.25 | 210 | 15.1087 | |
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| 0.2507 | 27.5 | 220 | 15.0569 | |
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| 0.2044 | 28.75 | 230 | 15.1893 | |
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| 0.1838 | 30.0 | 240 | 15.6291 | |
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| 0.1626 | 31.25 | 250 | 15.4617 | |
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| 0.1124 | 32.5 | 260 | 15.2738 | |
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| 0.1011 | 33.75 | 270 | 15.2130 | |
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| 0.0845 | 35.0 | 280 | 15.2749 | |
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| 0.0852 | 36.25 | 290 | 15.3292 | |
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| 0.1025 | 37.5 | 300 | 15.1574 | |
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| 0.1075 | 38.75 | 310 | 15.1100 | |
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| 0.079 | 40.0 | 320 | 14.8177 | |
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| 0.0857 | 41.25 | 330 | 14.8609 | |
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| 0.0629 | 42.5 | 340 | 14.6443 | |
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| 0.0713 | 43.75 | 350 | 14.5514 | |
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| 0.0594 | 45.0 | 360 | 14.6032 | |
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| 0.0557 | 46.25 | 370 | 14.3489 | |
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| 0.0554 | 47.5 | 380 | 14.3289 | |
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| 0.0548 | 48.75 | 390 | 14.1991 | |
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| 0.0528 | 50.0 | 400 | 14.1350 | |
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| 0.0515 | 51.25 | 410 | 13.9952 | |
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| 0.0529 | 52.5 | 420 | 13.9788 | |
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| 0.0516 | 53.75 | 430 | 13.9438 | |
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| 0.0506 | 55.0 | 440 | 13.8746 | |
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| 0.049 | 56.25 | 450 | 13.7564 | |
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| 0.0491 | 57.5 | 460 | 13.7900 | |
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| 0.0493 | 58.75 | 470 | 13.6992 | |
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| 0.0491 | 60.0 | 480 | 13.6421 | |
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| 0.0497 | 61.25 | 490 | 13.6419 | |
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| 0.0489 | 62.5 | 500 | 13.5448 | |
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| 0.0504 | 63.75 | 510 | 13.5048 | |
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| 0.0508 | 65.0 | 520 | 13.5077 | |
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| 0.0488 | 66.25 | 530 | 13.5045 | |
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| 0.0485 | 67.5 | 540 | 13.4404 | |
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| 0.0493 | 68.75 | 550 | 13.4167 | |
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| 0.0507 | 70.0 | 560 | 13.3758 | |
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| 0.0491 | 71.25 | 570 | 13.3239 | |
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| 0.0484 | 72.5 | 580 | 13.3139 | |
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| 0.0472 | 73.75 | 590 | 13.2933 | |
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| 0.0493 | 75.0 | 600 | 13.3105 | |
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| 0.0475 | 76.25 | 610 | 13.2306 | |
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| 0.0465 | 77.5 | 620 | 13.2378 | |
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| 0.0474 | 78.75 | 630 | 13.2074 | |
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| 0.0468 | 80.0 | 640 | 13.1871 | |
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| 0.0466 | 81.25 | 650 | 13.2055 | |
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| 0.0459 | 82.5 | 660 | 13.1327 | |
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| 0.0466 | 83.75 | 670 | 13.1801 | |
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| 0.0485 | 85.0 | 680 | 13.1610 | |
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| 0.046 | 86.25 | 690 | 13.1439 | |
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| 0.0467 | 87.5 | 700 | 13.1114 | |
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| 0.0455 | 88.75 | 710 | 13.1123 | |
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| 0.0456 | 90.0 | 720 | 13.0635 | |
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| 0.0447 | 91.25 | 730 | 13.0997 | |
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| 0.0449 | 92.5 | 740 | 13.0704 | |
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| 0.0453 | 93.75 | 750 | 13.0531 | |
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| 0.0451 | 95.0 | 760 | 13.0432 | |
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| 0.0442 | 96.25 | 770 | 13.0311 | |
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| 0.0444 | 97.5 | 780 | 13.0329 | |
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| 0.0432 | 98.75 | 790 | 13.0491 | |
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| 0.0442 | 100.0 | 800 | 13.0221 | |
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### Framework versions |
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- Transformers 4.39.1 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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