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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
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