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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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metrics: |
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- precision |
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- recall |
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- f1 |
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- accuracy |
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model-index: |
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- name: Team_Gryffindor_NER |
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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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# Team-Gryffindor-distilbert-base-finetuned-NER-creditcardcontract-100epoch |
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the Credit card agreement dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0470 |
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- Precision: 0.7319 |
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- Recall: 0.7064 |
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- F1: 0.7190 |
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- Accuracy: 0.9920 |
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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: 11 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
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|:-------------:|:-----:|:------:|:---------------:|:---------:|:------:|:------:|:--------:| |
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| 0.0113 | 0.33 | 500 | 0.0443 | 0.6547 | 0.7028 | 0.6779 | 0.9908 | |
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| 0.0118 | 0.67 | 1000 | 0.0435 | 0.7207 | 0.6440 | 0.6802 | 0.9916 | |
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| 0.013 | 1.0 | 1500 | 0.0449 | 0.7113 | 0.6826 | 0.6966 | 0.9918 | |
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| 0.0113 | 1.34 | 2000 | 0.0434 | 0.7213 | 0.6697 | 0.6946 | 0.9915 | |
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| 0.0121 | 1.67 | 2500 | 0.0467 | 0.6955 | 0.6789 | 0.6871 | 0.9914 | |
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| 0.0125 | 2.01 | 3000 | 0.0417 | 0.7095 | 0.6991 | 0.7043 | 0.9920 | |
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| 0.0106 | 2.34 | 3500 | 0.0437 | 0.7191 | 0.6624 | 0.6896 | 0.9918 | |
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| 0.0114 | 2.68 | 4000 | 0.0468 | 0.7165 | 0.6679 | 0.6914 | 0.9920 | |
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| 0.0125 | 3.01 | 4500 | 0.0431 | 0.6888 | 0.6862 | 0.6875 | 0.9917 | |
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| 0.0107 | 3.35 | 5000 | 0.0446 | 0.7184 | 0.6459 | 0.6802 | 0.9913 | |
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| 0.0096 | 3.68 | 5500 | 0.0485 | 0.6926 | 0.6532 | 0.6723 | 0.9912 | |
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| 0.013 | 4.02 | 6000 | 0.0448 | 0.6134 | 0.6697 | 0.6404 | 0.9907 | |
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| 0.0102 | 4.35 | 6500 | 0.0497 | 0.6895 | 0.6642 | 0.6766 | 0.9913 | |
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| 0.0112 | 4.69 | 7000 | 0.0464 | 0.6759 | 0.6697 | 0.6728 | 0.9910 | |
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| 0.0117 | 5.02 | 7500 | 0.0484 | 0.7451 | 0.6275 | 0.6813 | 0.9916 | |
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| 0.0114 | 5.36 | 8000 | 0.0411 | 0.7086 | 0.6826 | 0.6953 | 0.9919 | |
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| 0.0108 | 5.69 | 8500 | 0.0443 | 0.7041 | 0.6679 | 0.6855 | 0.9916 | |
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| 0.0109 | 6.03 | 9000 | 0.0470 | 0.7228 | 0.6697 | 0.6952 | 0.9916 | |
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| 0.0099 | 6.36 | 9500 | 0.0471 | 0.7253 | 0.6881 | 0.7062 | 0.9913 | |
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| 0.0103 | 6.7 | 10000 | 0.0430 | 0.6986 | 0.7101 | 0.7043 | 0.9914 | |
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| 0.0117 | 7.03 | 10500 | 0.0462 | 0.7327 | 0.6991 | 0.7155 | 0.9918 | |
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| 0.0098 | 7.37 | 11000 | 0.0483 | 0.6910 | 0.6771 | 0.6840 | 0.9914 | |
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| 0.0107 | 7.7 | 11500 | 0.0468 | 0.7189 | 0.6899 | 0.7041 | 0.9916 | |
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| 0.0119 | 8.04 | 12000 | 0.0434 | 0.6970 | 0.6881 | 0.6925 | 0.9918 | |
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| 0.0112 | 8.37 | 12500 | 0.0469 | 0.7007 | 0.6917 | 0.6962 | 0.9918 | |
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| 0.011 | 8.71 | 13000 | 0.0469 | 0.6736 | 0.6514 | 0.6623 | 0.9914 | |
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| 0.0101 | 9.04 | 13500 | 0.0451 | 0.6691 | 0.6606 | 0.6648 | 0.9913 | |
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| 0.0099 | 9.38 | 14000 | 0.0462 | 0.7006 | 0.6826 | 0.6914 | 0.9918 | |
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| 0.0107 | 9.71 | 14500 | 0.0444 | 0.6840 | 0.6752 | 0.6796 | 0.9915 | |
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| 0.0118 | 10.05 | 15000 | 0.0457 | 0.7015 | 0.6771 | 0.6891 | 0.9918 | |
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| 0.0102 | 10.38 | 15500 | 0.0500 | 0.7413 | 0.6679 | 0.7027 | 0.9919 | |
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| 0.0107 | 10.72 | 16000 | 0.0470 | 0.7319 | 0.7064 | 0.7190 | 0.9920 | |
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### Framework versions |
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- Transformers 4.18.0 |
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- Pytorch 1.10.0+cu111 |
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- Datasets 2.0.0 |
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- Tokenizers 0.11.6 |
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