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--- |
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license: apache-2.0 |
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base_model: vietgpt/bert-30M-uncased |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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model-index: |
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- name: bert-30M-uncased-classification-fqa |
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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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# bert-30M-uncased-classification-fqa |
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This model is a fine-tuned version of [vietgpt/bert-30M-uncased](https://huggingface.co/vietgpt/bert-30M-uncased) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.8275 |
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- Accuracy: 0.9538 |
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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: 2e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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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: 50 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| No log | 1.0 | 110 | 5.2109 | 0.0051 | |
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| No log | 2.0 | 220 | 5.2109 | 0.0 | |
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| No log | 3.0 | 330 | 5.1842 | 0.0 | |
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| No log | 4.0 | 440 | 5.0942 | 0.0256 | |
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| 5.141 | 5.0 | 550 | 4.8190 | 0.0615 | |
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| 5.141 | 6.0 | 660 | 4.5678 | 0.1128 | |
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| 5.141 | 7.0 | 770 | 4.3158 | 0.2205 | |
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| 5.141 | 8.0 | 880 | 4.0876 | 0.3333 | |
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| 5.141 | 9.0 | 990 | 3.8774 | 0.4410 | |
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| 4.3509 | 10.0 | 1100 | 3.6849 | 0.5179 | |
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| 4.3509 | 11.0 | 1210 | 3.5020 | 0.6103 | |
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| 4.3509 | 12.0 | 1320 | 3.3304 | 0.6718 | |
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| 4.3509 | 13.0 | 1430 | 3.1628 | 0.7026 | |
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| 3.3612 | 14.0 | 1540 | 3.0022 | 0.7692 | |
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| 3.3612 | 15.0 | 1650 | 2.8528 | 0.7897 | |
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| 3.3612 | 16.0 | 1760 | 2.7042 | 0.8051 | |
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| 3.3612 | 17.0 | 1870 | 2.5607 | 0.8205 | |
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| 3.3612 | 18.0 | 1980 | 2.4300 | 0.8359 | |
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| 2.5735 | 19.0 | 2090 | 2.3086 | 0.8462 | |
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| 2.5735 | 20.0 | 2200 | 2.1888 | 0.8462 | |
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| 2.5735 | 21.0 | 2310 | 2.0762 | 0.8667 | |
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| 2.5735 | 22.0 | 2420 | 1.9736 | 0.8718 | |
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| 1.9651 | 23.0 | 2530 | 1.8741 | 0.8718 | |
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| 1.9651 | 24.0 | 2640 | 1.7797 | 0.9026 | |
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| 1.9651 | 25.0 | 2750 | 1.6888 | 0.9077 | |
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| 1.9651 | 26.0 | 2860 | 1.6092 | 0.9128 | |
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| 1.9651 | 27.0 | 2970 | 1.5296 | 0.9128 | |
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| 1.5059 | 28.0 | 3080 | 1.4617 | 0.9179 | |
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| 1.5059 | 29.0 | 3190 | 1.3951 | 0.9179 | |
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| 1.5059 | 30.0 | 3300 | 1.3362 | 0.9179 | |
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| 1.5059 | 31.0 | 3410 | 1.2752 | 0.9179 | |
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| 1.1862 | 32.0 | 3520 | 1.2268 | 0.9179 | |
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| 1.1862 | 33.0 | 3630 | 1.1743 | 0.9179 | |
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| 1.1862 | 34.0 | 3740 | 1.1333 | 0.9231 | |
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| 1.1862 | 35.0 | 3850 | 1.0918 | 0.9282 | |
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| 1.1862 | 36.0 | 3960 | 1.0535 | 0.9385 | |
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| 0.9586 | 37.0 | 4070 | 1.0206 | 0.9385 | |
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| 0.9586 | 38.0 | 4180 | 0.9899 | 0.9333 | |
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| 0.9586 | 39.0 | 4290 | 0.9638 | 0.9385 | |
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| 0.9586 | 40.0 | 4400 | 0.9418 | 0.9436 | |
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| 0.8104 | 41.0 | 4510 | 0.9163 | 0.9436 | |
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| 0.8104 | 42.0 | 4620 | 0.8983 | 0.9436 | |
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| 0.8104 | 43.0 | 4730 | 0.8811 | 0.9487 | |
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| 0.8104 | 44.0 | 4840 | 0.8657 | 0.9538 | |
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| 0.8104 | 45.0 | 4950 | 0.8551 | 0.9538 | |
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| 0.7164 | 46.0 | 5060 | 0.8448 | 0.9538 | |
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| 0.7164 | 47.0 | 5170 | 0.8384 | 0.9487 | |
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| 0.7164 | 48.0 | 5280 | 0.8326 | 0.9538 | |
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| 0.7164 | 49.0 | 5390 | 0.8289 | 0.9538 | |
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| 0.6757 | 50.0 | 5500 | 0.8275 | 0.9538 | |
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### Framework versions |
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- Transformers 4.37.1 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.1 |
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