End of training

README.md

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+---
+library_name: transformers
+license: mit
+base_model: dslim/bert-base-NER
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: bert-base-NER-model
+  results: []
+---
+
+<!-- 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-NER-model
+
+This model is a fine-tuned version of [dslim/bert-base-NER](https://huggingface.co/dslim/bert-base-NER) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3093
+- Precision: 0.5601
+- Recall: 0.4059
+- F1: 0.4707
+- Accuracy: 0.9488
+
+## 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: 16
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- num_epochs: 2
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| No log        | 1.0   | 213  | 0.3253          | 0.5176    | 0.4096 | 0.4573 | 0.9472   |
+| No log        | 2.0   | 426  | 0.3093          | 0.5601    | 0.4059 | 0.4707 | 0.9488   |
+
+
+### Framework versions
+
+- Transformers 4.46.2
+- Pytorch 2.5.0+cu121
+- Tokenizers 0.20.3

runs/Nov13_20-15-07_2e6fc3f95e8a/events.out.tfevents.1731528908.2e6fc3f95e8a.1720.2

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