---
library_name: transformers
license: mit
base_model: BAAI/bge-small-en-v1.5
tags:
- generated_from_trainer
model-index:
- name: bge-small-en-v1.5-2024-12-08_01-40-13-quality-weight-0.5
  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-v1.5-2024-12-08_01-40-13-quality-weight-0.5

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: 0.0194
- Spearman: 0.9296
- Pearson: 0.9282
- Mse: 0.0194

## 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    |
|:-------------:|:------:|:-----:|:---------------:|:--------:|:-------:|:------:|
| 0.0295        | 0.3998 | 1055  | 0.0259          | 0.9011   | 0.9003  | 0.0259 |
| 0.0247        | 0.7997 | 2110  | 0.0233          | 0.9112   | 0.9111  | 0.0233 |
| 0.0218        | 1.1995 | 3165  | 0.0227          | 0.9170   | 0.9169  | 0.0227 |
| 0.0213        | 1.5994 | 4220  | 0.0204          | 0.9226   | 0.9222  | 0.0204 |
| 0.019         | 1.9992 | 5275  | 0.0206          | 0.9240   | 0.9245  | 0.0206 |
| 0.0168        | 2.3991 | 6330  | 0.0199          | 0.9248   | 0.9265  | 0.0199 |
| 0.0155        | 2.7989 | 7385  | 0.0193          | 0.9268   | 0.9281  | 0.0193 |
| 0.0123        | 3.1988 | 8440  | 0.0195          | 0.9278   | 0.9273  | 0.0195 |
| 0.0134        | 3.5986 | 9495  | 0.0192          | 0.9289   | 0.9293  | 0.0192 |
| 0.0136        | 3.9985 | 10550 | 0.0190          | 0.9290   | 0.9296  | 0.0190 |
| 0.0103        | 4.3983 | 11605 | 0.0193          | 0.9291   | 0.9294  | 0.0193 |
| 0.0117        | 4.7982 | 12660 | 0.0193          | 0.9293   | 0.9295  | 0.0193 |


### Framework versions

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