---
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: bert-finetuned-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. -->

# bert-finetuned-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: 0.0872
- Precision: 0.9053
- Recall: 0.9278
- F1: 0.9164
- Accuracy: 0.9827

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.0608        | 1.0   | 1252  | 0.0888          | 0.8833    | 0.9068 | 0.8949 | 0.9791   |
| 0.0481        | 2.0   | 2504  | 0.0822          | 0.8849    | 0.9159 | 0.9001 | 0.9801   |
| 0.0387        | 3.0   | 3756  | 0.0822          | 0.9000    | 0.9189 | 0.9093 | 0.9816   |
| 0.0348        | 4.0   | 5008  | 0.0820          | 0.9000    | 0.9238 | 0.9117 | 0.9820   |
| 0.038         | 5.0   | 6260  | 0.0810          | 0.8979    | 0.9233 | 0.9104 | 0.9818   |
| 0.0202        | 6.0   | 7512  | 0.0872          | 0.9019    | 0.9249 | 0.9133 | 0.9813   |
| 0.0147        | 7.0   | 8764  | 0.0894          | 0.9024    | 0.9241 | 0.9131 | 0.9817   |
| 0.0357        | 8.0   | 10016 | 0.0880          | 0.9038    | 0.9253 | 0.9144 | 0.9822   |
| 0.0289        | 9.0   | 11268 | 0.0867          | 0.9056    | 0.9278 | 0.9165 | 0.9827   |
| 0.0115        | 10.0  | 12520 | 0.0872          | 0.9053    | 0.9278 | 0.9164 | 0.9827   |


### Framework versions

- Transformers 4.57.3
- Pytorch 2.9.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1