ViGLUE
Collection
A collection to store all the artifacts of the paper: ViGLUE: A Vietnamese General Language Understanding Benchmark and Analysis of Vietnamese LMs.
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145 items
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Updated
This model is a fine-tuned version of bert-base-multilingual-cased on the tmnam20/VieGLUE/QNLI dataset. It achieves the following results on the evaluation set:
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The following hyperparameters were used during training:
Training Loss | Epoch | Step | Validation Loss | Accuracy |
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0.3938 | 0.15 | 500 | 0.3494 | 0.8495 |
0.3712 | 0.31 | 1000 | 0.3266 | 0.8570 |
0.3837 | 0.46 | 1500 | 0.3174 | 0.8655 |
0.3466 | 0.61 | 2000 | 0.2957 | 0.8785 |
0.3084 | 0.76 | 2500 | 0.3093 | 0.8715 |
0.322 | 0.92 | 3000 | 0.2950 | 0.8731 |
0.273 | 1.07 | 3500 | 0.2872 | 0.8834 |
0.2628 | 1.22 | 4000 | 0.3110 | 0.8794 |
0.2732 | 1.37 | 4500 | 0.2910 | 0.8797 |
0.2592 | 1.53 | 5000 | 0.2855 | 0.8849 |
0.241 | 1.68 | 5500 | 0.2974 | 0.8861 |
0.2256 | 1.83 | 6000 | 0.2914 | 0.8850 |
0.2402 | 1.99 | 6500 | 0.2759 | 0.8883 |
0.1958 | 2.14 | 7000 | 0.3080 | 0.8880 |
0.1684 | 2.29 | 7500 | 0.3190 | 0.8847 |
0.1472 | 2.44 | 8000 | 0.3305 | 0.8871 |
0.1601 | 2.6 | 8500 | 0.3298 | 0.8836 |
0.1857 | 2.75 | 9000 | 0.3274 | 0.8847 |
0.1667 | 2.9 | 9500 | 0.3256 | 0.8841 |
Base model
google-bert/bert-base-multilingual-cased