---
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-conll2003-generic
  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-conll2003-generic

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: 0.0840
- Precision: 0.9839
- Recall: 0.9848
- F1: 0.9844
- Accuracy: 0.9826

## 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 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 |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.2134        | 1.0   | 1250  | 0.1334          | 0.9721    | 0.9729 | 0.9725 | 0.9699   |
| 0.1022        | 2.0   | 2500  | 0.0997          | 0.9802    | 0.9806 | 0.9804 | 0.9783   |
| 0.0651        | 3.0   | 3750  | 0.0805          | 0.9819    | 0.9822 | 0.9820 | 0.9805   |
| 0.0503        | 4.0   | 5000  | 0.0788          | 0.9828    | 0.9832 | 0.9830 | 0.9813   |
| 0.0395        | 5.0   | 6250  | 0.0793          | 0.9833    | 0.9835 | 0.9834 | 0.9816   |
| 0.0324        | 6.0   | 7500  | 0.0782          | 0.9840    | 0.9842 | 0.9841 | 0.9824   |
| 0.0257        | 7.0   | 8750  | 0.0810          | 0.9835    | 0.9847 | 0.9841 | 0.9824   |
| 0.0201        | 8.0   | 10000 | 0.0821          | 0.9840    | 0.9846 | 0.9843 | 0.9825   |
| 0.0174        | 9.0   | 11250 | 0.0834          | 0.9838    | 0.9846 | 0.9842 | 0.9824   |
| 0.0151        | 10.0  | 12500 | 0.0840          | 0.9839    | 0.9848 | 0.9844 | 0.9826   |


### Framework versions

- Transformers 4.57.0
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1