metadata
license: apache-2.0
base_model: vietgpt/bert-30M-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: bert-30M-uncased-classification-fqa
results: []
bert-30M-uncased-classification-fqa
This model is a fine-tuned version of vietgpt/bert-30M-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.8275
- Accuracy: 0.9538
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: 50
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 110 | 5.2109 | 0.0051 |
| No log | 2.0 | 220 | 5.2109 | 0.0 |
| No log | 3.0 | 330 | 5.1842 | 0.0 |
| No log | 4.0 | 440 | 5.0942 | 0.0256 |
| 5.141 | 5.0 | 550 | 4.8190 | 0.0615 |
| 5.141 | 6.0 | 660 | 4.5678 | 0.1128 |
| 5.141 | 7.0 | 770 | 4.3158 | 0.2205 |
| 5.141 | 8.0 | 880 | 4.0876 | 0.3333 |
| 5.141 | 9.0 | 990 | 3.8774 | 0.4410 |
| 4.3509 | 10.0 | 1100 | 3.6849 | 0.5179 |
| 4.3509 | 11.0 | 1210 | 3.5020 | 0.6103 |
| 4.3509 | 12.0 | 1320 | 3.3304 | 0.6718 |
| 4.3509 | 13.0 | 1430 | 3.1628 | 0.7026 |
| 3.3612 | 14.0 | 1540 | 3.0022 | 0.7692 |
| 3.3612 | 15.0 | 1650 | 2.8528 | 0.7897 |
| 3.3612 | 16.0 | 1760 | 2.7042 | 0.8051 |
| 3.3612 | 17.0 | 1870 | 2.5607 | 0.8205 |
| 3.3612 | 18.0 | 1980 | 2.4300 | 0.8359 |
| 2.5735 | 19.0 | 2090 | 2.3086 | 0.8462 |
| 2.5735 | 20.0 | 2200 | 2.1888 | 0.8462 |
| 2.5735 | 21.0 | 2310 | 2.0762 | 0.8667 |
| 2.5735 | 22.0 | 2420 | 1.9736 | 0.8718 |
| 1.9651 | 23.0 | 2530 | 1.8741 | 0.8718 |
| 1.9651 | 24.0 | 2640 | 1.7797 | 0.9026 |
| 1.9651 | 25.0 | 2750 | 1.6888 | 0.9077 |
| 1.9651 | 26.0 | 2860 | 1.6092 | 0.9128 |
| 1.9651 | 27.0 | 2970 | 1.5296 | 0.9128 |
| 1.5059 | 28.0 | 3080 | 1.4617 | 0.9179 |
| 1.5059 | 29.0 | 3190 | 1.3951 | 0.9179 |
| 1.5059 | 30.0 | 3300 | 1.3362 | 0.9179 |
| 1.5059 | 31.0 | 3410 | 1.2752 | 0.9179 |
| 1.1862 | 32.0 | 3520 | 1.2268 | 0.9179 |
| 1.1862 | 33.0 | 3630 | 1.1743 | 0.9179 |
| 1.1862 | 34.0 | 3740 | 1.1333 | 0.9231 |
| 1.1862 | 35.0 | 3850 | 1.0918 | 0.9282 |
| 1.1862 | 36.0 | 3960 | 1.0535 | 0.9385 |
| 0.9586 | 37.0 | 4070 | 1.0206 | 0.9385 |
| 0.9586 | 38.0 | 4180 | 0.9899 | 0.9333 |
| 0.9586 | 39.0 | 4290 | 0.9638 | 0.9385 |
| 0.9586 | 40.0 | 4400 | 0.9418 | 0.9436 |
| 0.8104 | 41.0 | 4510 | 0.9163 | 0.9436 |
| 0.8104 | 42.0 | 4620 | 0.8983 | 0.9436 |
| 0.8104 | 43.0 | 4730 | 0.8811 | 0.9487 |
| 0.8104 | 44.0 | 4840 | 0.8657 | 0.9538 |
| 0.8104 | 45.0 | 4950 | 0.8551 | 0.9538 |
| 0.7164 | 46.0 | 5060 | 0.8448 | 0.9538 |
| 0.7164 | 47.0 | 5170 | 0.8384 | 0.9487 |
| 0.7164 | 48.0 | 5280 | 0.8326 | 0.9538 |
| 0.7164 | 49.0 | 5390 | 0.8289 | 0.9538 |
| 0.6757 | 50.0 | 5500 | 0.8275 | 0.9538 |
Framework versions
- Transformers 4.37.1
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1