---
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: dl2_ner_hw2
  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. -->

# dl2_ner_hw2

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: 0.0814
- Precision: 0.8982
- Recall: 0.9239
- F1: 0.9109
- Accuracy: 0.9814

## 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: 16
- eval_batch_size: 16
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.4629        | 1.0   | 625  | 0.1731          | 0.7698    | 0.8211 | 0.7946 | 0.9629   |
| 0.1715        | 2.0   | 1250 | 0.1127          | 0.8544    | 0.8921 | 0.8729 | 0.9757   |
| 0.1158        | 3.0   | 1875 | 0.0934          | 0.8609    | 0.9093 | 0.8844 | 0.9774   |
| 0.0687        | 4.0   | 2500 | 0.0858          | 0.8854    | 0.9150 | 0.8999 | 0.9803   |
| 0.0559        | 5.0   | 3125 | 0.0845          | 0.8817    | 0.9185 | 0.8998 | 0.9790   |
| 0.0454        | 6.0   | 3750 | 0.0811          | 0.8853    | 0.9196 | 0.9021 | 0.9798   |
| 0.0432        | 7.0   | 4375 | 0.0816          | 0.8876    | 0.9226 | 0.9048 | 0.9802   |
| 0.0336        | 8.0   | 5000 | 0.0815          | 0.8983    | 0.9231 | 0.9105 | 0.9813   |
| 0.0304        | 9.0   | 5625 | 0.0816          | 0.9005    | 0.9241 | 0.9121 | 0.9815   |
| 0.0296        | 10.0  | 6250 | 0.0814          | 0.8982    | 0.9239 | 0.9109 | 0.9814   |


### Framework versions

- Transformers 4.51.3
- Pytorch 2.11.0+cu128
- Datasets 3.4.1
- Tokenizers 0.21.4