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--- |
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license: bigscience-bloom-rail-1.0 |
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library_name: peft |
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tags: |
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- generated_from_trainer |
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base_model: vlsp-2023-vllm/hoa-1b4 |
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model-index: |
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- name: hoa-1b4_model_kaggle_format |
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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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# hoa-1b4_model_kaggle_format |
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This model is a fine-tuned version of [vlsp-2023-vllm/hoa-1b4](https://huggingface.co/vlsp-2023-vllm/hoa-1b4) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5927 |
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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: 4e-05 |
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- train_batch_size: 1 |
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- eval_batch_size: 1 |
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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 | 65 | 2.6363 | |
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| No log | 2.0 | 130 | 1.8356 | |
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| No log | 3.0 | 195 | 1.3984 | |
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| No log | 4.0 | 260 | 1.1658 | |
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| No log | 5.0 | 325 | 0.9857 | |
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| No log | 6.0 | 390 | 0.8724 | |
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| No log | 7.0 | 455 | 0.8085 | |
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| 1.4171 | 8.0 | 520 | 0.7400 | |
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| 1.4171 | 9.0 | 585 | 0.6925 | |
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| 1.4171 | 10.0 | 650 | 0.6654 | |
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| 1.4171 | 11.0 | 715 | 0.6383 | |
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| 1.4171 | 12.0 | 780 | 0.6341 | |
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| 1.4171 | 13.0 | 845 | 0.6148 | |
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| 1.4171 | 14.0 | 910 | 0.5979 | |
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| 1.4171 | 15.0 | 975 | 0.6061 | |
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| 0.2596 | 16.0 | 1040 | 0.5960 | |
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| 0.2596 | 17.0 | 1105 | 0.5810 | |
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| 0.2596 | 18.0 | 1170 | 0.5812 | |
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| 0.2596 | 19.0 | 1235 | 0.5761 | |
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| 0.2596 | 20.0 | 1300 | 0.5724 | |
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| 0.2596 | 21.0 | 1365 | 0.5600 | |
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| 0.2596 | 22.0 | 1430 | 0.5927 | |
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| 0.2596 | 23.0 | 1495 | 0.5627 | |
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| 0.1245 | 24.0 | 1560 | 0.5500 | |
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| 0.1245 | 25.0 | 1625 | 0.5706 | |
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| 0.1245 | 26.0 | 1690 | 0.5551 | |
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| 0.1245 | 27.0 | 1755 | 0.5548 | |
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| 0.1245 | 28.0 | 1820 | 0.5573 | |
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| 0.1245 | 29.0 | 1885 | 0.5642 | |
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| 0.1245 | 30.0 | 1950 | 0.5712 | |
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| 0.0896 | 31.0 | 2015 | 0.5524 | |
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| 0.0896 | 32.0 | 2080 | 0.5644 | |
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| 0.0896 | 33.0 | 2145 | 0.5511 | |
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| 0.0896 | 34.0 | 2210 | 0.5648 | |
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| 0.0896 | 35.0 | 2275 | 0.5722 | |
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| 0.0896 | 36.0 | 2340 | 0.5619 | |
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| 0.0896 | 37.0 | 2405 | 0.5632 | |
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| 0.0896 | 38.0 | 2470 | 0.5628 | |
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| 0.0746 | 39.0 | 2535 | 0.5593 | |
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| 0.0746 | 40.0 | 2600 | 0.5624 | |
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| 0.0746 | 41.0 | 2665 | 0.5744 | |
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| 0.0746 | 42.0 | 2730 | 0.5525 | |
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| 0.0746 | 43.0 | 2795 | 0.5858 | |
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| 0.0746 | 44.0 | 2860 | 0.5615 | |
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| 0.0746 | 45.0 | 2925 | 0.5614 | |
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| 0.0746 | 46.0 | 2990 | 0.5678 | |
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| 0.0696 | 47.0 | 3055 | 0.5735 | |
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| 0.0696 | 48.0 | 3120 | 0.5674 | |
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| 0.0696 | 49.0 | 3185 | 0.5637 | |
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| 0.0696 | 50.0 | 3250 | 0.5623 | |
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| 0.0696 | 51.0 | 3315 | 0.5668 | |
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| 0.0696 | 52.0 | 3380 | 0.5625 | |
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| 0.0696 | 53.0 | 3445 | 0.5630 | |
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| 0.0636 | 54.0 | 3510 | 0.5675 | |
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| 0.0636 | 55.0 | 3575 | 0.5646 | |
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| 0.0636 | 56.0 | 3640 | 0.5702 | |
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| 0.0636 | 57.0 | 3705 | 0.5729 | |
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| 0.0636 | 58.0 | 3770 | 0.5745 | |
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| 0.0636 | 59.0 | 3835 | 0.5737 | |
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| 0.0636 | 60.0 | 3900 | 0.5724 | |
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| 0.0636 | 61.0 | 3965 | 0.5658 | |
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| 0.0579 | 62.0 | 4030 | 0.5759 | |
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| 0.0579 | 63.0 | 4095 | 0.5777 | |
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| 0.0579 | 64.0 | 4160 | 0.5722 | |
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| 0.0579 | 65.0 | 4225 | 0.5721 | |
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| 0.0579 | 66.0 | 4290 | 0.5772 | |
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| 0.0579 | 67.0 | 4355 | 0.5747 | |
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| 0.0579 | 68.0 | 4420 | 0.5800 | |
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| 0.0579 | 69.0 | 4485 | 0.5814 | |
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| 0.0557 | 70.0 | 4550 | 0.5777 | |
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| 0.0557 | 71.0 | 4615 | 0.5765 | |
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| 0.0557 | 72.0 | 4680 | 0.5790 | |
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| 0.0557 | 73.0 | 4745 | 0.5845 | |
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| 0.0557 | 74.0 | 4810 | 0.5788 | |
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| 0.0557 | 75.0 | 4875 | 0.5836 | |
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| 0.0557 | 76.0 | 4940 | 0.5911 | |
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| 0.052 | 77.0 | 5005 | 0.5841 | |
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| 0.052 | 78.0 | 5070 | 0.5822 | |
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| 0.052 | 79.0 | 5135 | 0.5828 | |
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| 0.052 | 80.0 | 5200 | 0.5868 | |
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| 0.052 | 81.0 | 5265 | 0.5858 | |
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| 0.052 | 82.0 | 5330 | 0.5899 | |
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| 0.052 | 83.0 | 5395 | 0.5888 | |
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| 0.052 | 84.0 | 5460 | 0.5871 | |
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| 0.0478 | 85.0 | 5525 | 0.5867 | |
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| 0.0478 | 86.0 | 5590 | 0.5894 | |
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| 0.0478 | 87.0 | 5655 | 0.5899 | |
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| 0.0478 | 88.0 | 5720 | 0.5899 | |
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| 0.0478 | 89.0 | 5785 | 0.5915 | |
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| 0.0478 | 90.0 | 5850 | 0.5901 | |
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| 0.0478 | 91.0 | 5915 | 0.5919 | |
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| 0.0478 | 92.0 | 5980 | 0.5919 | |
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| 0.0458 | 93.0 | 6045 | 0.5916 | |
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| 0.0458 | 94.0 | 6110 | 0.5914 | |
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| 0.0458 | 95.0 | 6175 | 0.5929 | |
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| 0.0458 | 96.0 | 6240 | 0.5920 | |
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| 0.0458 | 97.0 | 6305 | 0.5922 | |
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| 0.0458 | 98.0 | 6370 | 0.5922 | |
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| 0.0458 | 99.0 | 6435 | 0.5924 | |
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| 0.0425 | 100.0 | 6500 | 0.5927 | |
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### Framework versions |
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- PEFT 0.9.0 |
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- Transformers 4.38.1 |
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- Pytorch 2.1.2 |
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- Datasets 2.1.0 |
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- Tokenizers 0.15.2 |
