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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: bert-base-multilingual-cased |
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tags: |
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- generated_from_trainer |
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datasets: |
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- turkish_ner |
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metrics: |
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- f1 |
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- precision |
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- recall |
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- accuracy |
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model-index: |
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- name: turkish-ner-mBERT-05 |
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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: turkish_ner |
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type: turkish_ner |
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config: default |
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split: train |
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args: default |
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metrics: |
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- name: F1 |
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type: f1 |
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value: 0.19467271181637857 |
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- name: Precision |
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type: precision |
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value: 0.3664 |
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- name: Recall |
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type: recall |
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value: 0.13254871695929 |
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- name: Accuracy |
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type: accuracy |
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value: 0.8172224930461962 |
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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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# turkish-ner-mBERT-05 |
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This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on the turkish_ner dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5967 |
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- F1: 0.1947 |
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- Precision: 0.3664 |
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- Recall: 0.1325 |
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- Accuracy: 0.8172 |
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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: 3e-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 OptimizerNames.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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- lr_scheduler_warmup_steps: 500 |
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- num_epochs: 5 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | F1 | Precision | Recall | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:---------:|:------:|:--------:| |
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| No log | 1.0 | 250 | 0.6886 | 0.0090 | 0.1702 | 0.0046 | 0.8144 | |
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| 0.8103 | 2.0 | 500 | 0.6445 | 0.1025 | 0.2930 | 0.0621 | 0.8158 | |
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| 0.8103 | 3.0 | 750 | 0.6265 | 0.1546 | 0.3204 | 0.1019 | 0.8130 | |
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| 0.5809 | 4.0 | 1000 | 0.5952 | 0.1790 | 0.3878 | 0.1163 | 0.8224 | |
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| 0.5809 | 5.0 | 1250 | 0.5967 | 0.1947 | 0.3664 | 0.1325 | 0.8172 | |
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### Framework versions |
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- Transformers 4.48.3 |
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- Pytorch 2.5.1+cu124 |
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- Datasets 3.3.2 |
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- Tokenizers 0.21.0 |
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