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bert-base-uncased-finetuned-ner

Token Classification
Transformers
PyTorch
bert
Generated from Trainer
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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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+ datasets:
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+ - generator
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+ model-index:
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+ - name: bert-base-uncased-finetuned-ner
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+ results: []
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+ ---
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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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+
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+ # bert-base-uncased-finetuned-ner
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+
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+ This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the generator dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.9799
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+ - Overall Precision: 0.4362
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+ - Overall Recall: 0.5285
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+ - Overall F1: 0.4779
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+ - Overall Accuracy: 0.9515
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+ - Datasetname F1: 0.3262
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+ - Hyperparametername F1: 0.7339
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+ - Hyperparametervalue F1: 0.7619
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+ - Methodname F1: 0.5193
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+ - Metricname F1: 0.6525
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+ - Metricvalue F1: 0.6452
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+ - Taskname F1: 0.2704
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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: 8
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+ - eval_batch_size: 8
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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: 100
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy | Datasetname F1 | Hyperparametername F1 | Hyperparametervalue F1 | Methodname F1 | Metricname F1 | Metricvalue F1 | Taskname F1 |
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+ |:-------------:|:-----:|:----:|:---------------:|:-----------------:|:--------------:|:----------:|:----------------:|:--------------:|:---------------------:|:----------------------:|:-------------:|:-------------:|:--------------:|:-----------:|
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+ | No log | 1.0 | 132 | 0.5733 | 0.2215 | 0.3313 | 0.2655 | 0.9350 | 0.0 | 0.1273 | 0.325 | 0.4369 | 0.2759 | 0.3478 | 0.0639 |
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+ | No log | 2.0 | 264 | 0.4130 | 0.2929 | 0.5996 | 0.3936 | 0.9348 | 0.2930 | 0.3316 | 0.6133 | 0.5104 | 0.5622 | 0.5263 | 0.2452 |
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+ | No log | 3.0 | 396 | 0.4654 | 0.3302 | 0.5793 | 0.4207 | 0.9431 | 0.2732 | 0.5 | 0.7463 | 0.5189 | 0.5930 | 0.5405 | 0.2228 |
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+ | 0.5901 | 4.0 | 528 | 0.4540 | 0.3604 | 0.5772 | 0.4438 | 0.9457 | 0.2644 | 0.5271 | 0.7027 | 0.5346 | 0.6386 | 0.4878 | 0.2804 |
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+ | 0.5901 | 5.0 | 660 | 0.5776 | 0.3920 | 0.5346 | 0.4523 | 0.9483 | 0.2529 | 0.6241 | 0.7761 | 0.5056 | 0.6369 | 0.6875 | 0.2601 |
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+ | 0.5901 | 6.0 | 792 | 0.4903 | 0.3934 | 0.6037 | 0.4763 | 0.9493 | 0.3651 | 0.6230 | 0.6667 | 0.5775 | 0.6136 | 0.4848 | 0.3084 |
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+ | 0.5901 | 7.0 | 924 | 0.6343 | 0.3991 | 0.5549 | 0.4643 | 0.9492 | 0.3286 | 0.6047 | 0.6301 | 0.5705 | 0.6216 | 0.5 | 0.2508 |
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+ | 0.1282 | 8.0 | 1056 | 0.6686 | 0.4185 | 0.5691 | 0.4823 | 0.9507 | 0.3546 | 0.6565 | 0.7353 | 0.5786 | 0.6174 | 0.4615 | 0.2540 |
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+ | 0.1282 | 9.0 | 1188 | 0.6801 | 0.4144 | 0.5610 | 0.4767 | 0.9507 | 0.3729 | 0.5616 | 0.7576 | 0.5569 | 0.5839 | 0.5263 | 0.2821 |
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+ | 0.1282 | 10.0 | 1320 | 0.5843 | 0.4022 | 0.5976 | 0.4808 | 0.9493 | 0.3262 | 0.6667 | 0.6957 | 0.5417 | 0.6267 | 0.6286 | 0.2969 |
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+ | 0.1282 | 11.0 | 1452 | 0.7041 | 0.4187 | 0.5813 | 0.4868 | 0.9508 | 0.3158 | 0.608 | 0.6857 | 0.5583 | 0.6174 | 0.7429 | 0.3145 |
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+ | 0.0579 | 12.0 | 1584 | 0.7037 | 0.4143 | 0.5894 | 0.4866 | 0.9509 | 0.3310 | 0.6032 | 0.7164 | 0.5426 | 0.6497 | 0.6486 | 0.3207 |
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+ | 0.0579 | 13.0 | 1716 | 0.6623 | 0.3961 | 0.5732 | 0.4684 | 0.9512 | 0.3490 | 0.6847 | 0.6462 | 0.5411 | 0.5987 | 0.6286 | 0.3038 |
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+ | 0.0579 | 14.0 | 1848 | 0.7953 | 0.4443 | 0.5752 | 0.5013 | 0.9517 | 0.3704 | 0.6457 | 0.6667 | 0.5705 | 0.625 | 0.6667 | 0.3030 |
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+ | 0.0579 | 15.0 | 1980 | 0.7321 | 0.4050 | 0.5976 | 0.4828 | 0.9482 | 0.3023 | 0.7156 | 0.7042 | 0.5815 | 0.6309 | 0.6667 | 0.2935 |
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+ | 0.0281 | 16.0 | 2112 | 0.7175 | 0.4149 | 0.6240 | 0.4984 | 0.9503 | 0.3740 | 0.5816 | 0.6667 | 0.5756 | 0.6335 | 0.6667 | 0.3182 |
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+ | 0.0281 | 17.0 | 2244 | 0.7463 | 0.4242 | 0.5915 | 0.4941 | 0.9507 | 0.3741 | 0.7130 | 0.7429 | 0.5678 | 0.6144 | 0.6486 | 0.2824 |
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+ | 0.0281 | 18.0 | 2376 | 0.8040 | 0.4172 | 0.5732 | 0.4829 | 0.9531 | 0.3485 | 0.6838 | 0.7647 | 0.4946 | 0.6279 | 0.6286 | 0.3233 |
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+ | 0.0156 | 19.0 | 2508 | 0.8922 | 0.4365 | 0.5589 | 0.4902 | 0.9525 | 0.4 | 0.6607 | 0.7500 | 0.5455 | 0.6013 | 0.6316 | 0.2803 |
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+ | 0.0156 | 20.0 | 2640 | 0.8597 | 0.4072 | 0.5488 | 0.4675 | 0.9516 | 0.3333 | 0.6435 | 0.7213 | 0.5086 | 0.6536 | 0.5882 | 0.2975 |
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+ | 0.0156 | 21.0 | 2772 | 0.7927 | 0.3986 | 0.5752 | 0.4709 | 0.9518 | 0.3759 | 0.6107 | 0.6857 | 0.5048 | 0.6582 | 0.7273 | 0.2802 |
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+ | 0.0156 | 22.0 | 2904 | 0.9151 | 0.4234 | 0.5732 | 0.4870 | 0.9493 | 0.3590 | 0.7143 | 0.8060 | 0.5491 | 0.6174 | 0.7273 | 0.2305 |
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+ | 0.0102 | 23.0 | 3036 | 0.9133 | 0.4231 | 0.5813 | 0.4897 | 0.9502 | 0.3185 | 0.6357 | 0.7941 | 0.55 | 0.6795 | 0.6061 | 0.2754 |
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+ | 0.0102 | 24.0 | 3168 | 0.9799 | 0.4362 | 0.5285 | 0.4779 | 0.9515 | 0.3262 | 0.7339 | 0.7619 | 0.5193 | 0.6525 | 0.6452 | 0.2704 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.23.1
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+ - Pytorch 1.12.1+cu102
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+ - Datasets 2.6.1
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+ - Tokenizers 0.13.1