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README.md

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+---
+library_name: transformers
+license: mit
+base_model: BAAI/bge-small-en-v1.5
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: bge-small-ner
+  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. -->
+
+# bge-small-ner
+
+This model is a fine-tuned version of [BAAI/bge-small-en-v1.5](https://huggingface.co/BAAI/bge-small-en-v1.5) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2431
+- Precision: 0.7048
+- Recall: 0.7467
+- F1: 0.7252
+- Accuracy: 0.9526
+
+## 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: 64
+- eval_batch_size: 128
+- seed: 42
+- optimizer: Use OptimizerNames.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: 3
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.5112        | 1.0   | 157  | 0.4266          | 0.4157    | 0.5261 | 0.4644 | 0.9118   |
+| 0.314         | 2.0   | 314  | 0.2689          | 0.6887    | 0.7275 | 0.7076 | 0.9499   |
+| 0.2681        | 3.0   | 471  | 0.2431          | 0.7048    | 0.7467 | 0.7252 | 0.9526   |
+
+
+### Framework versions
+
+- Transformers 4.53.3
+- Pytorch 2.6.0+cu124
+- Datasets 4.1.1
+- Tokenizers 0.21.2