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---
license: apache-2.0
base_model: bert-base-cased
tags:
- generated_from_trainer
datasets:
- harem
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-base-cased-finetuned-ner
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: harem
type: harem
config: default
split: validation
args: default
metrics:
- name: Precision
type: precision
value: 0.3251366120218579
- name: Recall
type: recall
value: 0.34097421203438394
- name: F1
type: f1
value: 0.3328671328671328
- name: Accuracy
type: accuracy
value: 0.8684278684278685
---
<!-- 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. -->
# bert-base-cased-finetuned-ner
This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the harem dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5103
- Precision: 0.3251
- Recall: 0.3410
- F1: 0.3329
- Accuracy: 0.8684
## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 40
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log | 1.0 | 4 | 1.1734 | 0.0 | 0.0 | 0.0 | 0.8083 |
| No log | 2.0 | 8 | 0.9781 | 0.0 | 0.0 | 0.0 | 0.8086 |
| No log | 3.0 | 12 | 0.8915 | 0.0 | 0.0 | 0.0 | 0.8086 |
| No log | 4.0 | 16 | 0.7901 | 0.0 | 0.0 | 0.0 | 0.8086 |
| No log | 5.0 | 20 | 0.7202 | 0.0 | 0.0 | 0.0 | 0.8086 |
| No log | 6.0 | 24 | 0.6846 | 0.4286 | 0.0344 | 0.0637 | 0.8130 |
| No log | 7.0 | 28 | 0.6596 | 0.2014 | 0.0802 | 0.1148 | 0.8306 |
| No log | 8.0 | 32 | 0.6355 | 0.1615 | 0.0745 | 0.1020 | 0.8324 |
| No log | 9.0 | 36 | 0.6193 | 0.1571 | 0.0946 | 0.1181 | 0.8345 |
| No log | 10.0 | 40 | 0.6106 | 0.1295 | 0.1032 | 0.1148 | 0.8335 |
| No log | 11.0 | 44 | 0.5919 | 0.1680 | 0.1232 | 0.1421 | 0.8350 |
| No log | 12.0 | 48 | 0.5789 | 0.2051 | 0.1375 | 0.1647 | 0.8384 |
| No log | 13.0 | 52 | 0.5827 | 0.1611 | 0.1375 | 0.1484 | 0.8355 |
| No log | 14.0 | 56 | 0.5638 | 0.2281 | 0.1862 | 0.2050 | 0.8433 |
| No log | 15.0 | 60 | 0.5576 | 0.1879 | 0.1691 | 0.1780 | 0.8420 |
| No log | 16.0 | 64 | 0.5485 | 0.2110 | 0.1862 | 0.1979 | 0.8456 |
| No log | 17.0 | 68 | 0.5479 | 0.2401 | 0.2264 | 0.2330 | 0.8500 |
| No log | 18.0 | 72 | 0.5460 | 0.2406 | 0.2378 | 0.2392 | 0.8503 |
| No log | 19.0 | 76 | 0.5374 | 0.2531 | 0.2350 | 0.2437 | 0.8542 |
| No log | 20.0 | 80 | 0.5365 | 0.2364 | 0.2493 | 0.2427 | 0.8539 |
| No log | 21.0 | 84 | 0.5284 | 0.2462 | 0.2350 | 0.2405 | 0.8552 |
| No log | 22.0 | 88 | 0.5306 | 0.2812 | 0.2837 | 0.2825 | 0.8601 |
| No log | 23.0 | 92 | 0.5262 | 0.2722 | 0.2722 | 0.2722 | 0.8573 |
| No log | 24.0 | 96 | 0.5306 | 0.2447 | 0.2665 | 0.2551 | 0.8555 |
| No log | 25.0 | 100 | 0.5249 | 0.2785 | 0.3009 | 0.2893 | 0.8594 |
| No log | 26.0 | 104 | 0.5201 | 0.2801 | 0.2865 | 0.2833 | 0.8586 |
| No log | 27.0 | 108 | 0.5213 | 0.2806 | 0.2894 | 0.2849 | 0.8604 |
| No log | 28.0 | 112 | 0.5207 | 0.2732 | 0.2951 | 0.2837 | 0.8612 |
| No log | 29.0 | 116 | 0.5144 | 0.3027 | 0.3209 | 0.3115 | 0.8630 |
| No log | 30.0 | 120 | 0.5135 | 0.3073 | 0.3381 | 0.3220 | 0.8648 |
| No log | 31.0 | 124 | 0.5147 | 0.2953 | 0.3266 | 0.3102 | 0.8651 |
| No log | 32.0 | 128 | 0.5121 | 0.2937 | 0.3181 | 0.3054 | 0.8645 |
| No log | 33.0 | 132 | 0.5092 | 0.3061 | 0.3324 | 0.3187 | 0.8645 |
| No log | 34.0 | 136 | 0.5064 | 0.3342 | 0.3696 | 0.3510 | 0.8677 |
| No log | 35.0 | 140 | 0.5056 | 0.3191 | 0.3438 | 0.3310 | 0.8674 |
| No log | 36.0 | 144 | 0.5091 | 0.3023 | 0.3352 | 0.3179 | 0.8661 |
| No log | 37.0 | 148 | 0.5104 | 0.3061 | 0.3324 | 0.3187 | 0.8658 |
| No log | 38.0 | 152 | 0.5100 | 0.3152 | 0.3324 | 0.3236 | 0.8677 |
| No log | 39.0 | 156 | 0.5102 | 0.3243 | 0.3410 | 0.3324 | 0.8684 |
| No log | 40.0 | 160 | 0.5103 | 0.3251 | 0.3410 | 0.3329 | 0.8684 |
### Framework versions
- Transformers 4.32.1
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3
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