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--- |
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license: apache-2.0 |
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base_model: bert-base-cased |
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tags: |
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- generated_from_trainer |
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datasets: |
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- harem |
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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: bert-base-cased-finetuned-ner |
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results: |
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- task: |
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name: Token Classification |
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type: token-classification |
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dataset: |
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name: harem |
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type: harem |
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config: default |
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split: validation |
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args: default |
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metrics: |
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- name: Precision |
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type: precision |
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value: 0.3251366120218579 |
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- name: Recall |
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type: recall |
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value: 0.34097421203438394 |
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- name: F1 |
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type: f1 |
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value: 0.3328671328671328 |
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- name: Accuracy |
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type: accuracy |
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value: 0.8684278684278685 |
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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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# bert-base-cased-finetuned-ner |
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This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the harem dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5103 |
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- Precision: 0.3251 |
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- Recall: 0.3410 |
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- F1: 0.3329 |
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- Accuracy: 0.8684 |
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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: 32 |
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- eval_batch_size: 32 |
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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: 40 |
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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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| No log | 1.0 | 4 | 1.1734 | 0.0 | 0.0 | 0.0 | 0.8083 | |
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| No log | 2.0 | 8 | 0.9781 | 0.0 | 0.0 | 0.0 | 0.8086 | |
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| No log | 3.0 | 12 | 0.8915 | 0.0 | 0.0 | 0.0 | 0.8086 | |
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| No log | 4.0 | 16 | 0.7901 | 0.0 | 0.0 | 0.0 | 0.8086 | |
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| No log | 5.0 | 20 | 0.7202 | 0.0 | 0.0 | 0.0 | 0.8086 | |
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| No log | 6.0 | 24 | 0.6846 | 0.4286 | 0.0344 | 0.0637 | 0.8130 | |
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| No log | 7.0 | 28 | 0.6596 | 0.2014 | 0.0802 | 0.1148 | 0.8306 | |
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| No log | 8.0 | 32 | 0.6355 | 0.1615 | 0.0745 | 0.1020 | 0.8324 | |
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| No log | 9.0 | 36 | 0.6193 | 0.1571 | 0.0946 | 0.1181 | 0.8345 | |
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| No log | 10.0 | 40 | 0.6106 | 0.1295 | 0.1032 | 0.1148 | 0.8335 | |
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| No log | 11.0 | 44 | 0.5919 | 0.1680 | 0.1232 | 0.1421 | 0.8350 | |
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| No log | 12.0 | 48 | 0.5789 | 0.2051 | 0.1375 | 0.1647 | 0.8384 | |
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| No log | 13.0 | 52 | 0.5827 | 0.1611 | 0.1375 | 0.1484 | 0.8355 | |
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| No log | 14.0 | 56 | 0.5638 | 0.2281 | 0.1862 | 0.2050 | 0.8433 | |
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| No log | 15.0 | 60 | 0.5576 | 0.1879 | 0.1691 | 0.1780 | 0.8420 | |
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| No log | 16.0 | 64 | 0.5485 | 0.2110 | 0.1862 | 0.1979 | 0.8456 | |
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| No log | 17.0 | 68 | 0.5479 | 0.2401 | 0.2264 | 0.2330 | 0.8500 | |
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| No log | 18.0 | 72 | 0.5460 | 0.2406 | 0.2378 | 0.2392 | 0.8503 | |
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| No log | 19.0 | 76 | 0.5374 | 0.2531 | 0.2350 | 0.2437 | 0.8542 | |
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| No log | 20.0 | 80 | 0.5365 | 0.2364 | 0.2493 | 0.2427 | 0.8539 | |
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| No log | 21.0 | 84 | 0.5284 | 0.2462 | 0.2350 | 0.2405 | 0.8552 | |
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| No log | 22.0 | 88 | 0.5306 | 0.2812 | 0.2837 | 0.2825 | 0.8601 | |
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| No log | 23.0 | 92 | 0.5262 | 0.2722 | 0.2722 | 0.2722 | 0.8573 | |
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| No log | 24.0 | 96 | 0.5306 | 0.2447 | 0.2665 | 0.2551 | 0.8555 | |
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| No log | 25.0 | 100 | 0.5249 | 0.2785 | 0.3009 | 0.2893 | 0.8594 | |
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| No log | 26.0 | 104 | 0.5201 | 0.2801 | 0.2865 | 0.2833 | 0.8586 | |
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| No log | 27.0 | 108 | 0.5213 | 0.2806 | 0.2894 | 0.2849 | 0.8604 | |
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| No log | 28.0 | 112 | 0.5207 | 0.2732 | 0.2951 | 0.2837 | 0.8612 | |
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| No log | 29.0 | 116 | 0.5144 | 0.3027 | 0.3209 | 0.3115 | 0.8630 | |
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| No log | 30.0 | 120 | 0.5135 | 0.3073 | 0.3381 | 0.3220 | 0.8648 | |
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| No log | 31.0 | 124 | 0.5147 | 0.2953 | 0.3266 | 0.3102 | 0.8651 | |
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| No log | 32.0 | 128 | 0.5121 | 0.2937 | 0.3181 | 0.3054 | 0.8645 | |
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| No log | 33.0 | 132 | 0.5092 | 0.3061 | 0.3324 | 0.3187 | 0.8645 | |
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| No log | 34.0 | 136 | 0.5064 | 0.3342 | 0.3696 | 0.3510 | 0.8677 | |
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| No log | 35.0 | 140 | 0.5056 | 0.3191 | 0.3438 | 0.3310 | 0.8674 | |
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| No log | 36.0 | 144 | 0.5091 | 0.3023 | 0.3352 | 0.3179 | 0.8661 | |
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| No log | 37.0 | 148 | 0.5104 | 0.3061 | 0.3324 | 0.3187 | 0.8658 | |
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| No log | 38.0 | 152 | 0.5100 | 0.3152 | 0.3324 | 0.3236 | 0.8677 | |
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| No log | 39.0 | 156 | 0.5102 | 0.3243 | 0.3410 | 0.3324 | 0.8684 | |
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| No log | 40.0 | 160 | 0.5103 | 0.3251 | 0.3410 | 0.3329 | 0.8684 | |
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### Framework versions |
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- Transformers 4.32.1 |
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- Pytorch 2.0.0 |
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- Datasets 2.1.0 |
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- Tokenizers 0.13.3 |
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