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bert-base-multilingual-uncased-finetuned-hp
This model is a fine-tuned version of bert-base-multilingual-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.4747
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 100
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 2.6826 | 1.0 | 66 | 2.4979 |
| 2.4316 | 2.0 | 132 | 2.2737 |
| 2.2563 | 3.0 | 198 | 2.1285 |
| 2.1158 | 4.0 | 264 | 2.0855 |
| 2.0196 | 5.0 | 330 | 1.9913 |
| 1.9651 | 6.0 | 396 | 1.9124 |
| 1.8956 | 7.0 | 462 | 1.9461 |
| 1.856 | 8.0 | 528 | 1.9519 |
| 1.8146 | 9.0 | 594 | 1.8063 |
| 1.7675 | 10.0 | 660 | 1.8229 |
| 1.7473 | 11.0 | 726 | 1.8271 |
| 1.7069 | 12.0 | 792 | 1.8147 |
| 1.678 | 13.0 | 858 | 1.8209 |
| 1.6291 | 14.0 | 924 | 1.7894 |
| 1.6251 | 15.0 | 990 | 1.7851 |
| 1.5939 | 16.0 | 1056 | 1.7237 |
| 1.5635 | 17.0 | 1122 | 1.7627 |
| 1.5088 | 18.0 | 1188 | 1.7392 |
| 1.5136 | 19.0 | 1254 | 1.6703 |
| 1.4782 | 20.0 | 1320 | 1.6922 |
| 1.4714 | 21.0 | 1386 | 1.6810 |
| 1.4451 | 22.0 | 1452 | 1.6318 |
| 1.4399 | 23.0 | 1518 | 1.6579 |
| 1.4262 | 24.0 | 1584 | 1.6303 |
| 1.3736 | 25.0 | 1650 | 1.6777 |
| 1.3896 | 26.0 | 1716 | 1.6887 |
| 1.3508 | 27.0 | 1782 | 1.6420 |
| 1.3939 | 28.0 | 1848 | 1.6026 |
| 1.3334 | 29.0 | 1914 | 1.6820 |
| 1.3169 | 30.0 | 1980 | 1.6018 |
| 1.2857 | 31.0 | 2046 | 1.6437 |
| 1.3152 | 32.0 | 2112 | 1.5975 |
| 1.2835 | 33.0 | 2178 | 1.6155 |
| 1.2388 | 34.0 | 2244 | 1.6033 |
| 1.2591 | 35.0 | 2310 | 1.6100 |
| 1.246 | 36.0 | 2376 | 1.5424 |
| 1.2196 | 37.0 | 2442 | 1.6082 |
| 1.2341 | 38.0 | 2508 | 1.4954 |
| 1.196 | 39.0 | 2574 | 1.5132 |
| 1.2025 | 40.0 | 2640 | 1.5710 |
| 1.1778 | 41.0 | 2706 | 1.5356 |
| 1.1645 | 42.0 | 2772 | 1.5545 |
| 1.1729 | 43.0 | 2838 | 1.4637 |
| 1.1542 | 44.0 | 2904 | 1.5700 |
| 1.1505 | 45.0 | 2970 | 1.5840 |
| 1.1224 | 46.0 | 3036 | 1.5451 |
| 1.118 | 47.0 | 3102 | 1.6250 |
| 1.0997 | 48.0 | 3168 | 1.4816 |
| 1.109 | 49.0 | 3234 | 1.5641 |
| 1.1243 | 50.0 | 3300 | 1.5099 |
| 1.1159 | 51.0 | 3366 | 1.5584 |
| 1.0955 | 52.0 | 3432 | 1.5589 |
| 1.0557 | 53.0 | 3498 | 1.5601 |
| 1.0685 | 54.0 | 3564 | 1.5211 |
| 1.0674 | 55.0 | 3630 | 1.5651 |
| 1.0625 | 56.0 | 3696 | 1.5918 |
| 1.0403 | 57.0 | 3762 | 1.5817 |
| 1.0197 | 58.0 | 3828 | 1.4936 |
| 1.031 | 59.0 | 3894 | 1.5860 |
| 1.0364 | 60.0 | 3960 | 1.5774 |
| 1.0375 | 61.0 | 4026 | 1.5358 |
| 1.0127 | 62.0 | 4092 | 1.5451 |
| 0.9982 | 63.0 | 4158 | 1.5271 |
| 0.9949 | 64.0 | 4224 | 1.5242 |
| 0.9962 | 65.0 | 4290 | 1.5564 |
| 1.0084 | 66.0 | 4356 | 1.5668 |
| 1.0076 | 67.0 | 4422 | 1.5867 |
| 0.9892 | 68.0 | 4488 | 1.5238 |
| 0.9889 | 69.0 | 4554 | 1.5097 |
| 0.9932 | 70.0 | 4620 | 1.5491 |
| 0.9815 | 71.0 | 4686 | 1.4237 |
| 0.9777 | 72.0 | 4752 | 1.5569 |
| 0.9525 | 73.0 | 4818 | 1.5103 |
| 0.9607 | 74.0 | 4884 | 1.5665 |
| 0.9488 | 75.0 | 4950 | 1.5910 |
| 0.9492 | 76.0 | 5016 | 1.5779 |
| 0.9667 | 77.0 | 5082 | 1.5581 |
| 0.9495 | 78.0 | 5148 | 1.4898 |
| 0.9457 | 79.0 | 5214 | 1.5638 |
| 0.9511 | 80.0 | 5280 | 1.5825 |
| 0.9173 | 81.0 | 5346 | 1.5565 |
| 0.9209 | 82.0 | 5412 | 1.5550 |
| 0.9446 | 83.0 | 5478 | 1.5431 |
| 0.9479 | 84.0 | 5544 | 1.4988 |
| 0.8999 | 85.0 | 5610 | 1.5311 |
| 0.9096 | 86.0 | 5676 | 1.5187 |
| 0.9044 | 87.0 | 5742 | 1.4801 |
| 0.8849 | 88.0 | 5808 | 1.5176 |
| 0.9006 | 89.0 | 5874 | 1.5871 |
| 0.9038 | 90.0 | 5940 | 1.4757 |
| 0.9026 | 91.0 | 6006 | 1.5138 |
| 0.8935 | 92.0 | 6072 | 1.6166 |
| 0.8812 | 93.0 | 6138 | 1.5561 |
| 0.8725 | 94.0 | 6204 | 1.5315 |
| 0.8941 | 95.0 | 6270 | 1.5468 |
| 0.9013 | 96.0 | 6336 | 1.6091 |
| 0.9232 | 97.0 | 6402 | 1.5199 |
| 0.8891 | 98.0 | 6468 | 1.5210 |
| 0.8956 | 99.0 | 6534 | 1.4859 |
| 0.8876 | 100.0 | 6600 | 1.4610 |
Framework versions
- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1
