|
--- |
|
|
|
model-index: |
|
- name: qa-indo-math-k-v2 |
|
--- |
|
|
|
<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
|
should probably proofread and complete it, then remove this comment. --> |
|
|
|
# qa-indo-math-k-v2 |
|
|
|
This model was trained from scratch on an unkown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 1.9328 |
|
|
|
## 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 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | |
|
|:-------------:|:-----:|:----:|:---------------:| |
|
| No log | 1.0 | 80 | 0.7969 | |
|
| No log | 2.0 | 160 | 0.7612 | |
|
| No log | 3.0 | 240 | 0.7624 | |
|
| No log | 4.0 | 320 | 0.7424 | |
|
| No log | 5.0 | 400 | 0.7634 | |
|
| No log | 6.0 | 480 | 0.7415 | |
|
| 0.9241 | 7.0 | 560 | 0.7219 | |
|
| 0.9241 | 8.0 | 640 | 0.7792 | |
|
| 0.9241 | 9.0 | 720 | 0.7803 | |
|
| 0.9241 | 10.0 | 800 | 0.7666 | |
|
| 0.9241 | 11.0 | 880 | 0.7614 | |
|
| 0.9241 | 12.0 | 960 | 0.7616 | |
|
| 0.6373 | 13.0 | 1040 | 0.7673 | |
|
| 0.6373 | 14.0 | 1120 | 0.7818 | |
|
| 0.6373 | 15.0 | 1200 | 0.8030 | |
|
| 0.6373 | 16.0 | 1280 | 0.8021 | |
|
| 0.6373 | 17.0 | 1360 | 0.8025 | |
|
| 0.6373 | 18.0 | 1440 | 0.8628 | |
|
| 0.5614 | 19.0 | 1520 | 0.8616 | |
|
| 0.5614 | 20.0 | 1600 | 0.8739 | |
|
| 0.5614 | 21.0 | 1680 | 0.8647 | |
|
| 0.5614 | 22.0 | 1760 | 0.9006 | |
|
| 0.5614 | 23.0 | 1840 | 0.9560 | |
|
| 0.5614 | 24.0 | 1920 | 0.9395 | |
|
| 0.486 | 25.0 | 2000 | 0.9453 | |
|
| 0.486 | 26.0 | 2080 | 0.9569 | |
|
| 0.486 | 27.0 | 2160 | 1.0208 | |
|
| 0.486 | 28.0 | 2240 | 0.9860 | |
|
| 0.486 | 29.0 | 2320 | 0.9806 | |
|
| 0.486 | 30.0 | 2400 | 1.0681 | |
|
| 0.486 | 31.0 | 2480 | 1.1085 | |
|
| 0.4126 | 32.0 | 2560 | 1.1028 | |
|
| 0.4126 | 33.0 | 2640 | 1.1110 | |
|
| 0.4126 | 34.0 | 2720 | 1.1573 | |
|
| 0.4126 | 35.0 | 2800 | 1.1387 | |
|
| 0.4126 | 36.0 | 2880 | 1.2067 | |
|
| 0.4126 | 37.0 | 2960 | 1.2079 | |
|
| 0.3559 | 38.0 | 3040 | 1.2152 | |
|
| 0.3559 | 39.0 | 3120 | 1.2418 | |
|
| 0.3559 | 40.0 | 3200 | 1.2023 | |
|
| 0.3559 | 41.0 | 3280 | 1.2679 | |
|
| 0.3559 | 42.0 | 3360 | 1.3178 | |
|
| 0.3559 | 43.0 | 3440 | 1.3419 | |
|
| 0.3084 | 44.0 | 3520 | 1.4702 | |
|
| 0.3084 | 45.0 | 3600 | 1.3824 | |
|
| 0.3084 | 46.0 | 3680 | 1.4227 | |
|
| 0.3084 | 47.0 | 3760 | 1.3925 | |
|
| 0.3084 | 48.0 | 3840 | 1.4940 | |
|
| 0.3084 | 49.0 | 3920 | 1.4110 | |
|
| 0.2686 | 50.0 | 4000 | 1.4534 | |
|
| 0.2686 | 51.0 | 4080 | 1.4749 | |
|
| 0.2686 | 52.0 | 4160 | 1.5351 | |
|
| 0.2686 | 53.0 | 4240 | 1.5479 | |
|
| 0.2686 | 54.0 | 4320 | 1.4755 | |
|
| 0.2686 | 55.0 | 4400 | 1.5207 | |
|
| 0.2686 | 56.0 | 4480 | 1.5075 | |
|
| 0.2388 | 57.0 | 4560 | 1.5470 | |
|
| 0.2388 | 58.0 | 4640 | 1.5361 | |
|
| 0.2388 | 59.0 | 4720 | 1.5914 | |
|
| 0.2388 | 60.0 | 4800 | 1.6430 | |
|
| 0.2388 | 61.0 | 4880 | 1.6249 | |
|
| 0.2388 | 62.0 | 4960 | 1.5503 | |
|
| 0.2046 | 63.0 | 5040 | 1.6441 | |
|
| 0.2046 | 64.0 | 5120 | 1.6789 | |
|
| 0.2046 | 65.0 | 5200 | 1.6174 | |
|
| 0.2046 | 66.0 | 5280 | 1.6175 | |
|
| 0.2046 | 67.0 | 5360 | 1.6947 | |
|
| 0.2046 | 68.0 | 5440 | 1.6299 | |
|
| 0.1891 | 69.0 | 5520 | 1.7419 | |
|
| 0.1891 | 70.0 | 5600 | 1.8442 | |
|
| 0.1891 | 71.0 | 5680 | 1.8802 | |
|
| 0.1891 | 72.0 | 5760 | 1.8233 | |
|
| 0.1891 | 73.0 | 5840 | 1.8172 | |
|
| 0.1891 | 74.0 | 5920 | 1.8181 | |
|
| 0.1664 | 75.0 | 6000 | 1.8399 | |
|
| 0.1664 | 76.0 | 6080 | 1.8128 | |
|
| 0.1664 | 77.0 | 6160 | 1.8423 | |
|
| 0.1664 | 78.0 | 6240 | 1.8380 | |
|
| 0.1664 | 79.0 | 6320 | 1.8941 | |
|
| 0.1664 | 80.0 | 6400 | 1.8636 | |
|
| 0.1664 | 81.0 | 6480 | 1.7949 | |
|
| 0.1614 | 82.0 | 6560 | 1.8342 | |
|
| 0.1614 | 83.0 | 6640 | 1.8123 | |
|
| 0.1614 | 84.0 | 6720 | 1.8639 | |
|
| 0.1614 | 85.0 | 6800 | 1.8580 | |
|
| 0.1614 | 86.0 | 6880 | 1.8816 | |
|
| 0.1614 | 87.0 | 6960 | 1.8579 | |
|
| 0.1487 | 88.0 | 7040 | 1.8783 | |
|
| 0.1487 | 89.0 | 7120 | 1.9175 | |
|
| 0.1487 | 90.0 | 7200 | 1.9025 | |
|
| 0.1487 | 91.0 | 7280 | 1.9207 | |
|
| 0.1487 | 92.0 | 7360 | 1.9195 | |
|
| 0.1487 | 93.0 | 7440 | 1.9142 | |
|
| 0.1355 | 94.0 | 7520 | 1.9333 | |
|
| 0.1355 | 95.0 | 7600 | 1.9238 | |
|
| 0.1355 | 96.0 | 7680 | 1.9256 | |
|
| 0.1355 | 97.0 | 7760 | 1.9305 | |
|
| 0.1355 | 98.0 | 7840 | 1.9294 | |
|
| 0.1355 | 99.0 | 7920 | 1.9301 | |
|
| 0.1297 | 100.0 | 8000 | 1.9328 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.6.1 |
|
- Pytorch 1.7.0 |
|
- Datasets 1.11.0 |
|
- Tokenizers 0.10.3 |
|
|
