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---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: Team_Gryffindor_NER
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# Team-Gryffindor-distilbert-base-finetuned-NER-creditcardcontract-100epoch
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the Credit card agreement dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0470
- Precision: 0.7319
- Recall: 0.7064
- F1: 0.7190
- Accuracy: 0.9920
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 11
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:------:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.0113 | 0.33 | 500 | 0.0443 | 0.6547 | 0.7028 | 0.6779 | 0.9908 |
| 0.0118 | 0.67 | 1000 | 0.0435 | 0.7207 | 0.6440 | 0.6802 | 0.9916 |
| 0.013 | 1.0 | 1500 | 0.0449 | 0.7113 | 0.6826 | 0.6966 | 0.9918 |
| 0.0113 | 1.34 | 2000 | 0.0434 | 0.7213 | 0.6697 | 0.6946 | 0.9915 |
| 0.0121 | 1.67 | 2500 | 0.0467 | 0.6955 | 0.6789 | 0.6871 | 0.9914 |
| 0.0125 | 2.01 | 3000 | 0.0417 | 0.7095 | 0.6991 | 0.7043 | 0.9920 |
| 0.0106 | 2.34 | 3500 | 0.0437 | 0.7191 | 0.6624 | 0.6896 | 0.9918 |
| 0.0114 | 2.68 | 4000 | 0.0468 | 0.7165 | 0.6679 | 0.6914 | 0.9920 |
| 0.0125 | 3.01 | 4500 | 0.0431 | 0.6888 | 0.6862 | 0.6875 | 0.9917 |
| 0.0107 | 3.35 | 5000 | 0.0446 | 0.7184 | 0.6459 | 0.6802 | 0.9913 |
| 0.0096 | 3.68 | 5500 | 0.0485 | 0.6926 | 0.6532 | 0.6723 | 0.9912 |
| 0.013 | 4.02 | 6000 | 0.0448 | 0.6134 | 0.6697 | 0.6404 | 0.9907 |
| 0.0102 | 4.35 | 6500 | 0.0497 | 0.6895 | 0.6642 | 0.6766 | 0.9913 |
| 0.0112 | 4.69 | 7000 | 0.0464 | 0.6759 | 0.6697 | 0.6728 | 0.9910 |
| 0.0117 | 5.02 | 7500 | 0.0484 | 0.7451 | 0.6275 | 0.6813 | 0.9916 |
| 0.0114 | 5.36 | 8000 | 0.0411 | 0.7086 | 0.6826 | 0.6953 | 0.9919 |
| 0.0108 | 5.69 | 8500 | 0.0443 | 0.7041 | 0.6679 | 0.6855 | 0.9916 |
| 0.0109 | 6.03 | 9000 | 0.0470 | 0.7228 | 0.6697 | 0.6952 | 0.9916 |
| 0.0099 | 6.36 | 9500 | 0.0471 | 0.7253 | 0.6881 | 0.7062 | 0.9913 |
| 0.0103 | 6.7 | 10000 | 0.0430 | 0.6986 | 0.7101 | 0.7043 | 0.9914 |
| 0.0117 | 7.03 | 10500 | 0.0462 | 0.7327 | 0.6991 | 0.7155 | 0.9918 |
| 0.0098 | 7.37 | 11000 | 0.0483 | 0.6910 | 0.6771 | 0.6840 | 0.9914 |
| 0.0107 | 7.7 | 11500 | 0.0468 | 0.7189 | 0.6899 | 0.7041 | 0.9916 |
| 0.0119 | 8.04 | 12000 | 0.0434 | 0.6970 | 0.6881 | 0.6925 | 0.9918 |
| 0.0112 | 8.37 | 12500 | 0.0469 | 0.7007 | 0.6917 | 0.6962 | 0.9918 |
| 0.011 | 8.71 | 13000 | 0.0469 | 0.6736 | 0.6514 | 0.6623 | 0.9914 |
| 0.0101 | 9.04 | 13500 | 0.0451 | 0.6691 | 0.6606 | 0.6648 | 0.9913 |
| 0.0099 | 9.38 | 14000 | 0.0462 | 0.7006 | 0.6826 | 0.6914 | 0.9918 |
| 0.0107 | 9.71 | 14500 | 0.0444 | 0.6840 | 0.6752 | 0.6796 | 0.9915 |
| 0.0118 | 10.05 | 15000 | 0.0457 | 0.7015 | 0.6771 | 0.6891 | 0.9918 |
| 0.0102 | 10.38 | 15500 | 0.0500 | 0.7413 | 0.6679 | 0.7027 | 0.9919 |
| 0.0107 | 10.72 | 16000 | 0.0470 | 0.7319 | 0.7064 | 0.7190 | 0.9920 |
### Framework versions
- Transformers 4.18.0
- Pytorch 1.10.0+cu111
- Datasets 2.0.0
- Tokenizers 0.11.6
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