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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: 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
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