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: dbmdz/bert-base-turkish-cased
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tags:
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- generated_from_trainer
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metrics:
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- accuracy
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model-index:
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- name: text-mod-token-classification-40000-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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# text-mod-token-classification-40000-finetuned-ner
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This model is a fine-tuned version of [dbmdz/bert-base-turkish-cased](https://huggingface.co/dbmdz/bert-base-turkish-cased) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0525
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- Accuracy: 0.9880
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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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: linear
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- num_epochs: 6
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| 0.037 | 1.0 | 143 | 0.0627 | 0.9754 |
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| 0.0191 | 2.0 | 286 | 0.0560 | 0.9788 |
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| 0.0343 | 3.0 | 429 | 0.0495 | 0.9840 |
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| 0.0082 | 4.0 | 572 | 0.0478 | 0.9853 |
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| 0.0066 | 5.0 | 715 | 0.0504 | 0.9882 |
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| 0.0012 | 6.0 | 858 | 0.0525 | 0.9880 |
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### Framework versions
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- Transformers 4.46.3
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- Pytorch 2.5.1+cu121
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- Datasets 3.2.0
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- Tokenizers 0.20.3
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runs/Dec12_21-54-29_8d7c853a4131/events.out.tfevents.1734040472.8d7c853a4131.345.0
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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size
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version https://git-lfs.github.com/spec/v1
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size 188051
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