sinhala_albert
This model is a fine-tuned version of albert-base-v2 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 4.5337
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: 5e-05
- train_batch_size: 128
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 100
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.0056 | 1.0 | 83 | 1.0130 |
| 0.9992 | 2.0 | 166 | 1.0021 |
| 0.9774 | 3.0 | 249 | 0.9789 |
| 0.9323 | 4.0 | 332 | 0.9695 |
| 0.863 | 5.0 | 415 | 0.9616 |
| 0.7944 | 6.0 | 498 | 0.9871 |
| 0.6328 | 7.0 | 581 | 1.0075 |
| 0.4705 | 8.0 | 664 | 1.4911 |
| 0.2834 | 9.0 | 747 | 1.5777 |
| 0.2278 | 10.0 | 830 | 1.6406 |
| 0.1751 | 11.0 | 913 | 1.7568 |
| 0.1657 | 12.0 | 996 | 1.7089 |
| 0.0974 | 13.0 | 1079 | 1.8463 |
| 0.1562 | 14.0 | 1162 | 1.9219 |
| 0.118 | 15.0 | 1245 | 1.9384 |
| 0.1044 | 16.0 | 1328 | 1.9971 |
| 0.0952 | 17.0 | 1411 | 2.1732 |
| 0.0877 | 18.0 | 1494 | 2.0566 |
| 0.0598 | 19.0 | 1577 | 2.4616 |
| 0.0762 | 20.0 | 1660 | 2.2672 |
| 0.1003 | 21.0 | 1743 | 2.3471 |
| 0.0627 | 22.0 | 1826 | 2.2526 |
| 0.0584 | 23.0 | 1909 | 2.7092 |
| 0.0679 | 24.0 | 1992 | 2.1629 |
| 0.0538 | 25.0 | 2075 | 2.5745 |
| 0.0723 | 26.0 | 2158 | 2.5667 |
| 0.0564 | 27.0 | 2241 | 2.4331 |
| 0.0662 | 28.0 | 2324 | 2.7811 |
| 0.0226 | 29.0 | 2407 | 2.8163 |
| 0.0224 | 30.0 | 2490 | 2.7452 |
| 0.0344 | 31.0 | 2573 | 2.6642 |
| 0.0519 | 32.0 | 2656 | 2.3490 |
| 0.0478 | 33.0 | 2739 | 2.7382 |
| 0.0436 | 34.0 | 2822 | 2.7556 |
| 0.0474 | 35.0 | 2905 | 2.5449 |
| 0.0355 | 36.0 | 2988 | 2.8280 |
| 0.0343 | 37.0 | 3071 | 2.9405 |
| 0.0283 | 38.0 | 3154 | 2.9870 |
| 0.0446 | 39.0 | 3237 | 3.0252 |
| 0.0288 | 40.0 | 3320 | 3.0866 |
| 0.0134 | 41.0 | 3403 | 3.1549 |
| 0.0328 | 42.0 | 3486 | 3.0168 |
| 0.0159 | 43.0 | 3569 | 2.8753 |
| 0.0155 | 44.0 | 3652 | 3.3455 |
| 0.0087 | 45.0 | 3735 | 3.4373 |
| 0.0296 | 46.0 | 3818 | 3.1949 |
| 0.0085 | 47.0 | 3901 | 3.1817 |
| 0.0048 | 48.0 | 3984 | 3.2233 |
| 0.0122 | 49.0 | 4067 | 3.5465 |
| 0.0024 | 50.0 | 4150 | 3.5276 |
| 0.0014 | 51.0 | 4233 | 3.5111 |
| 0.0121 | 52.0 | 4316 | 3.4483 |
| 0.0159 | 53.0 | 4399 | 3.8072 |
| 0.0027 | 54.0 | 4482 | 3.7448 |
| 0.0059 | 55.0 | 4565 | 3.9230 |
| 0.0083 | 56.0 | 4648 | 3.9245 |
| 0.0128 | 57.0 | 4731 | 3.8699 |
| 0.0116 | 58.0 | 4814 | 3.9957 |
| 0.0013 | 59.0 | 4897 | 3.8153 |
| 0.0013 | 60.0 | 4980 | 3.9093 |
| 0.0035 | 61.0 | 5063 | 4.0339 |
| 0.0028 | 62.0 | 5146 | 3.9929 |
| 0.0036 | 63.0 | 5229 | 4.1217 |
| 0.004 | 64.0 | 5312 | 4.0936 |
| 0.0014 | 65.0 | 5395 | 4.1109 |
| 0.0047 | 66.0 | 5478 | 4.1978 |
| 0.0005 | 67.0 | 5561 | 4.2320 |
| 0.0009 | 68.0 | 5644 | 4.2441 |
| 0.0027 | 69.0 | 5727 | 4.2670 |
| 0.0008 | 70.0 | 5810 | 4.2923 |
| 0.0013 | 71.0 | 5893 | 4.3101 |
| 0.0006 | 72.0 | 5976 | 4.3561 |
| 0.0024 | 73.0 | 6059 | 4.3419 |
| 0.0014 | 74.0 | 6142 | 4.3432 |
| 0.0011 | 75.0 | 6225 | 4.3302 |
| 0.0 | 76.0 | 6308 | 4.3439 |
| 0.0016 | 77.0 | 6391 | 4.3667 |
| 0.0026 | 78.0 | 6474 | 4.3803 |
| 0.0031 | 79.0 | 6557 | 4.3800 |
| 0.002 | 80.0 | 6640 | 4.3941 |
| 0.0008 | 81.0 | 6723 | 4.4071 |
| 0.0019 | 82.0 | 6806 | 4.4259 |
| 0.0013 | 83.0 | 6889 | 4.4436 |
| 0.0015 | 84.0 | 6972 | 4.4603 |
| 0.0009 | 85.0 | 7055 | 4.4706 |
| 0.0019 | 86.0 | 7138 | 4.4701 |
| 0.001 | 87.0 | 7221 | 4.4777 |
| 0.0007 | 88.0 | 7304 | 4.4905 |
| 0.0021 | 89.0 | 7387 | 4.4910 |
| 0.0012 | 90.0 | 7470 | 4.4959 |
| 0.0 | 91.0 | 7553 | 4.4990 |
| 0.0024 | 92.0 | 7636 | 4.5091 |
| 0.0031 | 93.0 | 7719 | 4.5115 |
| 0.0011 | 94.0 | 7802 | 4.5215 |
| 0.0 | 95.0 | 7885 | 4.5152 |
| 0.002 | 96.0 | 7968 | 4.5200 |
| 0.0013 | 97.0 | 8051 | 4.5293 |
| 0.0013 | 98.0 | 8134 | 4.5285 |
| 0.0023 | 99.0 | 8217 | 4.5339 |
| 0.002 | 100.0 | 8300 | 4.5337 |
Framework versions
- Transformers 4.41.0.dev0
- Pytorch 2.2.1+cu118
- Datasets 2.14.5
- Tokenizers 0.19.1