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tmnam20/bert-base-multilingual-cased-qnli-100
bert-base-multilingual-cased-qnli-100 is a text classification model from tmnam20. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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From the Hugging Face model README
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:
More information needed
More information needed
More information needed
The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.4041 | 0.15 | 500 | 0.3611 | 0.8488 |
| 0.3784 | 0.31 | 1000 | 0.3232 | 0.8603 |
| 0.364 | 0.46 | 1500 | 0.3128 | 0.8642 |
| 0.364 | 0.61 | 2000 | 0.3020 | 0.8702 |
| 0.3236 | 0.76 | 2500 | 0.2960 | 0.8768 |
| 0.3475 | 0.92 | 3000 | 0.2895 | 0.8816 |
| 0.252 | 1.07 | 3500 | 0.3019 | 0.8812 |
| 0.261 | 1.22 | 4000 | 0.2783 | 0.8893 |
| 0.2718 | 1.37 | 4500 | 0.2880 | 0.8832 |
| 0.2407 | 1.53 | 5000 | 0.3017 | 0.8812 |
| 0.254 | 1.68 | 5500 | 0.2775 | 0.8827 |
| 0.2611 | 1.83 | 6000 | 0.2837 | 0.8812 |
| 0.257 | 1.99 | 6500 | 0.2816 | 0.8852 |
| 0.1645 | 2.14 | 7000 | 0.3323 | 0.8845 |
| 0.1679 | 2.29 | 7500 | 0.3568 | 0.8825 |
| 0.1643 | 2.44 | 8000 | 0.3203 | 0.8889 |
| 0.1662 | 2.6 | 8500 | 0.3240 | 0.8878 |
| 0.1558 | 2.75 | 9000 | 0.3302 | 0.8856 |
| 0.1614 | 2.9 | 9500 | 0.3299 | 0.8872 |