---
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: exp
  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. -->

# exp

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: 0.0837
- Precision: 0.9039
- Recall: 0.9278
- F1: 0.9157
- Accuracy: 0.9820

## 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_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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.0754        | 1.0   | 625  | 0.0876          | 0.8654    | 0.9130 | 0.8885 | 0.9783   |
| 0.0514        | 2.0   | 1250 | 0.0818          | 0.8857    | 0.9197 | 0.9024 | 0.9804   |
| 0.0502        | 3.0   | 1875 | 0.0800          | 0.8866    | 0.9174 | 0.9017 | 0.9799   |
| 0.0250        | 4.0   | 2500 | 0.0806          | 0.8915    | 0.9222 | 0.9066 | 0.9805   |
| 0.0260        | 5.0   | 3125 | 0.0843          | 0.8904    | 0.9244 | 0.9071 | 0.9802   |
| 0.0208        | 6.0   | 3750 | 0.0800          | 0.9006    | 0.9281 | 0.9141 | 0.9817   |
| 0.0202        | 7.0   | 4375 | 0.0810          | 0.8998    | 0.9291 | 0.9142 | 0.9822   |
| 0.0140        | 8.0   | 5000 | 0.0813          | 0.9083    | 0.9281 | 0.9181 | 0.9826   |
| 0.0140        | 9.0   | 5625 | 0.0840          | 0.9034    | 0.9290 | 0.9160 | 0.9819   |
| 0.0167        | 10.0  | 6250 | 0.0837          | 0.9039    | 0.9278 | 0.9157 | 0.9820   |


### Framework versions

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