---
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: 0.0826
- Precision: 0.8830
- Recall: 0.9180
- F1: 0.9002
- Accuracy: 0.9805

## 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: 32
- eval_batch_size: 32
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 313  | 0.2444          | 0.6772    | 0.7282 | 0.7018 | 0.9494   |
| 0.4390        | 2.0   | 626  | 0.1448          | 0.8205    | 0.8686 | 0.8439 | 0.9711   |
| 0.4390        | 3.0   | 939  | 0.1147          | 0.8479    | 0.8972 | 0.8719 | 0.9759   |
| 0.1424        | 4.0   | 1252 | 0.0982          | 0.8746    | 0.9063 | 0.8902 | 0.9791   |
| 0.0895        | 5.0   | 1565 | 0.0930          | 0.8725    | 0.9090 | 0.8904 | 0.9791   |
| 0.0895        | 6.0   | 1878 | 0.0868          | 0.8871    | 0.9128 | 0.8998 | 0.9805   |
| 0.0656        | 7.0   | 2191 | 0.0855          | 0.8763    | 0.9180 | 0.8967 | 0.9800   |
| 0.0565        | 8.0   | 2504 | 0.0843          | 0.8821    | 0.9164 | 0.8989 | 0.9803   |
| 0.0565        | 9.0   | 2817 | 0.0830          | 0.8830    | 0.9187 | 0.9005 | 0.9806   |
| 0.0485        | 10.0  | 3130 | 0.0826          | 0.8830    | 0.9180 | 0.9002 | 0.9805   |


### Framework versions

- Transformers 5.2.0
- Pytorch 2.10.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2