---
library_name: transformers
license: mit
base_model: BAAI/bge-small-en-v1.5
tags:
- generated_from_trainer
model-index:
- name: bge-small-en-v1.5-2024-12-06_14-23-52-relevancy-1
  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. -->

# bge-small-en-v1.5-2024-12-06_14-23-52-relevancy-1

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: 0.0219
- Spearman: 0.9313
- Pearson: 0.9323
- Mse: 0.0219

## 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: 5e-05
- train_batch_size: 64
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 256
- 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: cosine
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 5

### Training results

| Training Loss | Epoch  | Step  | Validation Loss | Spearman | Pearson | Mse    |
|:-------------:|:------:|:-----:|:---------------:|:--------:|:-------:|:------:|
| 0.0334        | 0.3998 | 1055  | 0.0291          | 0.9039   | 0.9070  | 0.0291 |
| 0.0276        | 0.7997 | 2110  | 0.0264          | 0.9129   | 0.9165  | 0.0264 |
| 0.0244        | 1.1995 | 3165  | 0.0253          | 0.9185   | 0.9215  | 0.0253 |
| 0.0239        | 1.5994 | 4220  | 0.0230          | 0.9235   | 0.9271  | 0.0230 |
| 0.0217        | 1.9992 | 5275  | 0.0234          | 0.9252   | 0.9294  | 0.0234 |
| 0.0186        | 2.3991 | 6330  | 0.0228          | 0.9272   | 0.9304  | 0.0228 |
| 0.0174        | 2.7989 | 7385  | 0.0219          | 0.9286   | 0.9320  | 0.0219 |
| 0.0136        | 3.1988 | 8440  | 0.0221          | 0.9290   | 0.9314  | 0.0221 |
| 0.014         | 3.5986 | 9495  | 0.0218          | 0.9304   | 0.9329  | 0.0218 |
| 0.0149        | 3.9985 | 10550 | 0.0215          | 0.9305   | 0.9332  | 0.0215 |
| 0.0112        | 4.3983 | 11605 | 0.0217          | 0.9305   | 0.9332  | 0.0217 |
| 0.0127        | 4.7982 | 12660 | 0.0217          | 0.9306   | 0.9333  | 0.0217 |


### Framework versions

- Transformers 4.46.3
- Pytorch 2.4.1+cu121
- Datasets 2.19.2
- Tokenizers 0.20.3