---
license: mit
base_model: BAAI/bge-small-zh-v1.5
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: sft-bge-bert24m-to-sentiment
  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. -->

# sft-bge-bert24m-to-sentiment

This model is a fine-tuned version of [BAAI/bge-small-zh-v1.5](https://huggingface.co/BAAI/bge-small-zh-v1.5) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5564
- Accuracy: 0.7853

## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.5355        | 1.0   | 3750  | 0.5576          | 0.7633   |
| 0.4901        | 2.0   | 7500  | 0.5481          | 0.779    |
| 0.4494        | 3.0   | 11250 | 0.5340          | 0.7793   |
| 0.4305        | 4.0   | 15000 | 0.5467          | 0.7797   |
| 0.3995        | 5.0   | 18750 | 0.5564          | 0.7853   |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.2.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2