| ---
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| library_name: transformers
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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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| 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-finetuned-ner
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| results: []
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| ---
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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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|
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| # bert-finetuned-ner
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| This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on an unknown dataset.
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| It achieves the following results on the evaluation set:
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| - Loss: 0.0580
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| - Precision: 0.9345
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| - Recall: 0.9509
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| - F1: 0.9426
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| - Accuracy: 0.9870
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|
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| ## Model description
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| More information needed
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|
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| ## Intended uses & limitations
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| More information needed
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|
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| ## Training and evaluation data
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| More information needed
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|
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| ## Training procedure
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|
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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: 8
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| - eval_batch_size: 8
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| - seed: 42
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| - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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: 3
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|
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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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| | 0.0745 | 1.0 | 1756 | 0.0693 | 0.9033 | 0.9335 | 0.9181 | 0.9805 |
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| | 0.0343 | 2.0 | 3512 | 0.0655 | 0.9337 | 0.9477 | 0.9406 | 0.9858 |
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| | 0.0212 | 3.0 | 5268 | 0.0580 | 0.9345 | 0.9509 | 0.9426 | 0.9870 |
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| ### Framework versions
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| - Transformers 4.57.3
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| - Pytorch 2.9.1+cu130
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| - Datasets 4.4.1
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| - Tokenizers 0.22.1
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| |
