---
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: 0.0890
- Precision: 0.9050
- Recall: 0.9287
- F1: 0.9167
- Accuracy: 0.9828

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.0647        | 1.0   | 1250  | 0.0937          | 0.8574    | 0.9124 | 0.8840 | 0.9769   |
| 0.0465        | 2.0   | 2500  | 0.0914          | 0.8914    | 0.9156 | 0.9033 | 0.9802   |
| 0.0351        | 3.0   | 3750  | 0.0871          | 0.8950    | 0.9168 | 0.9058 | 0.9814   |
| 0.0298        | 4.0   | 5000  | 0.0891          | 0.8966    | 0.9262 | 0.9111 | 0.9816   |
| 0.025         | 5.0   | 6250  | 0.0888          | 0.8962    | 0.9282 | 0.9119 | 0.9819   |
| 0.0193        | 6.0   | 7500  | 0.0836          | 0.9068    | 0.9291 | 0.9178 | 0.9827   |
| 0.0165        | 7.0   | 8750  | 0.0874          | 0.9051    | 0.9292 | 0.9170 | 0.9829   |
| 0.0132        | 8.0   | 10000 | 0.0890          | 0.9050    | 0.9287 | 0.9167 | 0.9828   |


### Framework versions

- Transformers 4.56.2
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1