Model save
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README.md
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---
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library_name: transformers
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license: mit
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base_model: akdeniz27/bert-base-turkish-cased-ner
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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: bert-base-turkish-cased-ner-finetuned-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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# bert-base-turkish-cased-ner-finetuned-ner
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This model is a fine-tuned version of [akdeniz27/bert-base-turkish-cased-ner](https://huggingface.co/akdeniz27/bert-base-turkish-cased-ner) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1768
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- Precision: 0.9689
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- Recall: 0.9688
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- F1: 0.9688
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- Accuracy: 0.9711
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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: 1e-05
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- train_batch_size: 6
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- eval_batch_size: 6
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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: 5
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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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| 0.1616 | 1.0 | 3334 | 0.1414 | 0.9622 | 0.9624 | 0.9623 | 0.9651 |
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| 0.1143 | 2.0 | 6668 | 0.1483 | 0.9667 | 0.9672 | 0.9670 | 0.9694 |
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| 0.0957 | 3.0 | 10002 | 0.1531 | 0.9680 | 0.9682 | 0.9681 | 0.9705 |
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| 0.0488 | 4.0 | 13336 | 0.1720 | 0.9690 | 0.9688 | 0.9689 | 0.9713 |
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| 0.03 | 5.0 | 16670 | 0.1768 | 0.9689 | 0.9688 | 0.9688 | 0.9711 |
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### Framework versions
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- Transformers 4.44.2
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- Pytorch 2.4.0+cu121
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- Datasets 2.21.0
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- Tokenizers 0.19.1
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runs/Aug31_19-31-35_2c536c84e717/events.out.tfevents.1725132768.2c536c84e717.1912.0
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