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--- |
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library_name: transformers |
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license: agpl-3.0 |
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base_model: vinai/phobert-base-v2 |
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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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- f1 |
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model-index: |
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- name: PhoBert_Lexical_Dataset45K |
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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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# PhoBert_Lexical_Dataset45K |
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This model is a fine-tuned version of [vinai/phobert-base-v2](https://huggingface.co/vinai/phobert-base-v2) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4880 |
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- Accuracy: 0.8851 |
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- F1: 0.8858 |
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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: 64 |
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- eval_batch_size: 64 |
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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: 15 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |
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|:-------------:|:-------:|:-----:|:---------------:|:--------:|:------:| |
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| No log | 0.2841 | 200 | 0.3476 | 0.8474 | 0.8494 | |
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| No log | 0.5682 | 400 | 0.3035 | 0.8692 | 0.8703 | |
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| No log | 0.8523 | 600 | 0.3132 | 0.8654 | 0.8674 | |
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| 0.3678 | 1.1364 | 800 | 0.2832 | 0.8797 | 0.8797 | |
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| 0.3678 | 1.4205 | 1000 | 0.2805 | 0.8828 | 0.8815 | |
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| 0.3678 | 1.7045 | 1200 | 0.2622 | 0.8862 | 0.8874 | |
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| 0.3678 | 1.9886 | 1400 | 0.2751 | 0.8898 | 0.8889 | |
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| 0.2662 | 2.2727 | 1600 | 0.2627 | 0.8873 | 0.8886 | |
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| 0.2662 | 2.5568 | 1800 | 0.2514 | 0.8945 | 0.8940 | |
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| 0.2662 | 2.8409 | 2000 | 0.2433 | 0.8941 | 0.8949 | |
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| 0.219 | 3.125 | 2200 | 0.2600 | 0.8914 | 0.8922 | |
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| 0.219 | 3.4091 | 2400 | 0.2563 | 0.8933 | 0.8937 | |
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| 0.219 | 3.6932 | 2600 | 0.2592 | 0.8909 | 0.8919 | |
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| 0.219 | 3.9773 | 2800 | 0.2390 | 0.8969 | 0.8974 | |
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| 0.1865 | 4.2614 | 3000 | 0.2925 | 0.8820 | 0.8834 | |
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| 0.1865 | 4.5455 | 3200 | 0.2922 | 0.8871 | 0.8883 | |
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| 0.1865 | 4.8295 | 3400 | 0.2975 | 0.8838 | 0.8854 | |
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| 0.1591 | 5.1136 | 3600 | 0.2935 | 0.8920 | 0.8926 | |
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| 0.1591 | 5.3977 | 3800 | 0.2860 | 0.8893 | 0.8901 | |
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| 0.1591 | 5.6818 | 4000 | 0.2943 | 0.8939 | 0.8940 | |
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| 0.1591 | 5.9659 | 4200 | 0.2898 | 0.8970 | 0.8973 | |
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| 0.1394 | 6.25 | 4400 | 0.3268 | 0.8886 | 0.8886 | |
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| 0.1394 | 6.5341 | 4600 | 0.3399 | 0.8804 | 0.8820 | |
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| 0.1394 | 6.8182 | 4800 | 0.3353 | 0.8887 | 0.8894 | |
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| 0.1159 | 7.1023 | 5000 | 0.3313 | 0.8950 | 0.8956 | |
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| 0.1159 | 7.3864 | 5200 | 0.3496 | 0.8955 | 0.8956 | |
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| 0.1159 | 7.6705 | 5400 | 0.3509 | 0.8920 | 0.8925 | |
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| 0.1159 | 7.9545 | 5600 | 0.3534 | 0.8842 | 0.8855 | |
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| 0.1005 | 8.2386 | 5800 | 0.3529 | 0.8932 | 0.8936 | |
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| 0.1005 | 8.5227 | 6000 | 0.3641 | 0.8914 | 0.8916 | |
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| 0.1005 | 8.8068 | 6200 | 0.3572 | 0.8907 | 0.8911 | |
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| 0.0838 | 9.0909 | 6400 | 0.4026 | 0.8873 | 0.8873 | |
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| 0.0838 | 9.375 | 6600 | 0.4049 | 0.8869 | 0.8876 | |
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| 0.0838 | 9.6591 | 6800 | 0.4024 | 0.8808 | 0.8822 | |
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| 0.0838 | 9.9432 | 7000 | 0.4161 | 0.8874 | 0.8886 | |
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| 0.0732 | 10.2273 | 7200 | 0.4098 | 0.8881 | 0.8885 | |
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| 0.0732 | 10.5114 | 7400 | 0.4010 | 0.8880 | 0.8885 | |
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| 0.0732 | 10.7955 | 7600 | 0.4166 | 0.8890 | 0.8891 | |
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| 0.0616 | 11.0795 | 7800 | 0.4317 | 0.8853 | 0.8859 | |
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| 0.0616 | 11.3636 | 8000 | 0.4323 | 0.8878 | 0.8884 | |
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| 0.0616 | 11.6477 | 8200 | 0.4550 | 0.8862 | 0.8872 | |
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| 0.0616 | 11.9318 | 8400 | 0.4509 | 0.8882 | 0.8890 | |
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| 0.0547 | 12.2159 | 8600 | 0.4463 | 0.8871 | 0.8877 | |
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| 0.0547 | 12.5 | 8800 | 0.4705 | 0.8842 | 0.8849 | |
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| 0.0547 | 12.7841 | 9000 | 0.4663 | 0.8876 | 0.8880 | |
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| 0.0472 | 13.0682 | 9200 | 0.4825 | 0.8867 | 0.8876 | |
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| 0.0472 | 13.3523 | 9400 | 0.4796 | 0.8858 | 0.8864 | |
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| 0.0472 | 13.6364 | 9600 | 0.4856 | 0.8853 | 0.8862 | |
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| 0.0472 | 13.9205 | 9800 | 0.4896 | 0.8840 | 0.8851 | |
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| 0.0433 | 14.2045 | 10000 | 0.4810 | 0.8859 | 0.8864 | |
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| 0.0433 | 14.4886 | 10200 | 0.4900 | 0.8842 | 0.8851 | |
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| 0.0433 | 14.7727 | 10400 | 0.4880 | 0.8851 | 0.8858 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.1.2 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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