---
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: dl_hw2
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# dl_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: 0.1198
- Precision: 0.8429
- Recall: 0.8869
- F1: 0.8644
- Accuracy: 0.9744

## 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: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.4371        | 1.0   | 625  | 0.1932          | 0.7403    | 0.7906 | 0.7646 | 0.9579   |
| 0.1659        | 2.0   | 1250 | 0.1319          | 0.8343    | 0.8748 | 0.8541 | 0.9727   |
| 0.1236        | 3.0   | 1875 | 0.1198          | 0.8429    | 0.8869 | 0.8644 | 0.9744   |


### Framework versions

- Transformers 4.53.3
- Pytorch 2.6.0+cu124
- Datasets 4.1.1
- Tokenizers 0.21.2