---
library_name: transformers
license: mit
base_model: BAAI/bge-small-en-v1.5
tags:
- generated_from_trainer
model-index:
- name: bge-small-en-v1.5-2024-12-07_18-39-49-quality-weight-0.4
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# bge-small-en-v1.5-2024-12-07_18-39-49-quality-weight-0.4

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: 0.0199
- Spearman: 0.9293
- Pearson: 0.9291
- Mse: 0.0199

## 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    |
|:-------------:|:------:|:-----:|:---------------:|:--------:|:-------:|:------:|
| 0.0301        | 0.3998 | 1055  | 0.0265          | 0.9008   | 0.9017  | 0.0265 |
| 0.0253        | 0.7997 | 2110  | 0.0238          | 0.9108   | 0.9126  | 0.0238 |
| 0.0222        | 1.1995 | 3165  | 0.0231          | 0.9164   | 0.9179  | 0.0231 |
| 0.0217        | 1.5994 | 4220  | 0.0209          | 0.9222   | 0.9232  | 0.0209 |
| 0.0195        | 1.9992 | 5275  | 0.0211          | 0.9234   | 0.9254  | 0.0211 |
| 0.0171        | 2.3991 | 6330  | 0.0204          | 0.9244   | 0.9275  | 0.0204 |
| 0.0159        | 2.7989 | 7385  | 0.0197          | 0.9265   | 0.9291  | 0.0197 |
| 0.0124        | 3.1988 | 8440  | 0.0200          | 0.9274   | 0.9282  | 0.0200 |
| 0.0135        | 3.5986 | 9495  | 0.0196          | 0.9285   | 0.9301  | 0.0196 |
| 0.014         | 3.9985 | 10550 | 0.0194          | 0.9285   | 0.9304  | 0.0194 |
| 0.0103        | 4.3983 | 11605 | 0.0197          | 0.9287   | 0.9302  | 0.0197 |
| 0.0119        | 4.7982 | 12660 | 0.0197          | 0.9289   | 0.9303  | 0.0197 |


### Framework versions

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