---
library_name: transformers
license: mit
base_model: BAAI/bge-small-en-v1.5
tags:
- ner
- token-classification
- bge
- baai
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: ner-bge-small-en-v1_5_baseline
  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. -->

# ner-bge-small-en-v1_5_baseline

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: 0.1337
- Precision: 0.9271
- Recall: 0.9352
- F1: 0.9311
- Accuracy: 0.9832

## 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: 4.969409787289472e-05
- train_batch_size: 4
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.0214        | 1.0   | 2503  | 0.1404          | 0.8961    | 0.9221 | 0.9089 | 0.9800   |
| 0.0041        | 2.0   | 5006  | 0.1326          | 0.9071    | 0.9236 | 0.9153 | 0.9806   |
| 0.0089        | 3.0   | 7509  | 0.1329          | 0.9024    | 0.9211 | 0.9116 | 0.9794   |
| 0.0256        | 4.0   | 10012 | 0.1220          | 0.9081    | 0.9263 | 0.9171 | 0.9814   |
| 0.0289        | 5.0   | 12515 | 0.1229          | 0.9159    | 0.9293 | 0.9226 | 0.9825   |
| 0.0038        | 6.0   | 15018 | 0.1333          | 0.9206    | 0.9285 | 0.9245 | 0.9819   |
| 0.0015        | 7.0   | 17521 | 0.1353          | 0.9239    | 0.9355 | 0.9297 | 0.9831   |
| 0.0021        | 8.0   | 20024 | 0.1352          | 0.9207    | 0.9335 | 0.9270 | 0.9827   |
| 0.0003        | 9.0   | 22527 | 0.1307          | 0.9216    | 0.9357 | 0.9286 | 0.9832   |
| 0.001         | 10.0  | 25030 | 0.1337          | 0.9271    | 0.9352 | 0.9311 | 0.9832   |


### Framework versions

- Transformers 4.57.0
- Pytorch 2.8.0+cu128
- Datasets 4.2.0
- Tokenizers 0.22.1