---
library_name: transformers
license: mit
base_model: BAAI/bge-base-en-v1.5
tags:
- generated_from_trainer
model-index:
- name: bge-base-en-v1.5-2024-12-28_14-02-19-quality-weight-0.6
  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-base-en-v1.5-2024-12-28_14-02-19-quality-weight-0.6

This model is a fine-tuned version of [BAAI/bge-base-en-v1.5](https://huggingface.co/BAAI/bge-base-en-v1.5) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0186
- Spearman: 0.9302
- Pearson: 0.9279
- Mse: 0.0186

## 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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 64
- 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    |
|:-------------:|:------:|:-----:|:---------------:|:--------:|:-------:|:------:|
| 0.0375        | 0.0997 | 263   | 0.0382          | 0.8522   | 0.8465  | 0.0382 |
| 0.0365        | 0.1994 | 526   | 0.0339          | 0.8742   | 0.8658  | 0.0339 |
| 0.043         | 0.2990 | 789   | 0.0319          | 0.8810   | 0.8754  | 0.0319 |
| 0.0283        | 0.3987 | 1052  | 0.0322          | 0.8905   | 0.8817  | 0.0322 |
| 0.0319        | 0.4984 | 1315  | 0.0295          | 0.8962   | 0.8914  | 0.0295 |
| 0.02          | 0.5981 | 1578  | 0.0278          | 0.8984   | 0.8968  | 0.0278 |
| 0.0334        | 0.6978 | 1841  | 0.0246          | 0.9046   | 0.9025  | 0.0246 |
| 0.0272        | 0.7975 | 2104  | 0.0263          | 0.9070   | 0.9033  | 0.0263 |
| 0.0295        | 0.8971 | 2367  | 0.0235          | 0.9068   | 0.9067  | 0.0235 |
| 0.0208        | 0.9968 | 2630  | 0.0227          | 0.9103   | 0.9097  | 0.0227 |
| 0.0238        | 1.0963 | 2893  | 0.0241          | 0.9129   | 0.9105  | 0.0241 |
| 0.023         | 1.1960 | 3156  | 0.0226          | 0.9135   | 0.9117  | 0.0226 |
| 0.0168        | 1.2956 | 3419  | 0.0223          | 0.9164   | 0.9140  | 0.0223 |
| 0.0182        | 1.3953 | 3682  | 0.0213          | 0.9183   | 0.9162  | 0.0213 |
| 0.0189        | 1.4950 | 3945  | 0.0214          | 0.9185   | 0.9174  | 0.0214 |
| 0.018         | 1.5947 | 4208  | 0.0209          | 0.9183   | 0.9184  | 0.0209 |
| 0.0148        | 1.6944 | 4471  | 0.0209          | 0.9198   | 0.9188  | 0.0209 |
| 0.0137        | 1.7940 | 4734  | 0.0204          | 0.9210   | 0.9210  | 0.0204 |
| 0.021         | 1.8937 | 4997  | 0.0204          | 0.9205   | 0.9208  | 0.0204 |
| 0.0212        | 1.9934 | 5260  | 0.0204          | 0.9227   | 0.9226  | 0.0204 |
| 0.0099        | 2.0929 | 5523  | 0.0198          | 0.9235   | 0.9229  | 0.0198 |
| 0.0128        | 2.1925 | 5786  | 0.0199          | 0.9231   | 0.9224  | 0.0199 |
| 0.0116        | 2.2922 | 6049  | 0.0198          | 0.9244   | 0.9219  | 0.0198 |
| 0.0145        | 2.3919 | 6312  | 0.0200          | 0.9226   | 0.9222  | 0.0200 |
| 0.0157        | 2.4916 | 6575  | 0.0204          | 0.9249   | 0.9235  | 0.0204 |
| 0.0104        | 2.5913 | 6838  | 0.0196          | 0.9253   | 0.9248  | 0.0196 |
| 0.0118        | 2.6910 | 7101  | 0.0194          | 0.9243   | 0.9245  | 0.0194 |
| 0.0108        | 2.7906 | 7364  | 0.0193          | 0.9267   | 0.9265  | 0.0193 |
| 0.0171        | 2.8903 | 7627  | 0.0188          | 0.9259   | 0.9268  | 0.0188 |
| 0.0087        | 2.9900 | 7890  | 0.0190          | 0.9275   | 0.9272  | 0.0190 |
| 0.0093        | 3.0894 | 8153  | 0.0188          | 0.9277   | 0.9271  | 0.0188 |
| 0.01          | 3.1891 | 8416  | 0.0190          | 0.9279   | 0.9268  | 0.0190 |
| 0.0117        | 3.2888 | 8679  | 0.0186          | 0.9277   | 0.9273  | 0.0186 |
| 0.0143        | 3.3885 | 8942  | 0.0189          | 0.9281   | 0.9273  | 0.0189 |
| 0.0088        | 3.4882 | 9205  | 0.0187          | 0.9284   | 0.9280  | 0.0187 |
| 0.008         | 3.5879 | 9468  | 0.0191          | 0.9288   | 0.9278  | 0.0191 |
| 0.0102        | 3.6875 | 9731  | 0.0185          | 0.9290   | 0.9285  | 0.0185 |
| 0.0079        | 3.7872 | 9994  | 0.0186          | 0.9291   | 0.9282  | 0.0186 |
| 0.0105        | 3.8869 | 10257 | 0.0184          | 0.9290   | 0.9282  | 0.0184 |
| 0.0138        | 3.9866 | 10520 | 0.0185          | 0.9294   | 0.9285  | 0.0185 |
| 0.0078        | 4.0860 | 10783 | 0.0187          | 0.9293   | 0.9285  | 0.0187 |
| 0.0064        | 4.1857 | 11046 | 0.0185          | 0.9296   | 0.9287  | 0.0185 |
| 0.008         | 4.2854 | 11309 | 0.0186          | 0.9293   | 0.9284  | 0.0186 |
| 0.0081        | 4.3851 | 11572 | 0.0184          | 0.9297   | 0.9288  | 0.0184 |
| 0.007         | 4.4848 | 11835 | 0.0185          | 0.9297   | 0.9287  | 0.0185 |
| 0.0075        | 4.5845 | 12098 | 0.0185          | 0.9299   | 0.9290  | 0.0185 |
| 0.0072        | 4.6841 | 12361 | 0.0186          | 0.9298   | 0.9287  | 0.0186 |
| 0.0067        | 4.7838 | 12624 | 0.0185          | 0.9298   | 0.9287  | 0.0185 |
| 0.0084        | 4.8835 | 12887 | 0.0185          | 0.9298   | 0.9288  | 0.0185 |
| 0.007         | 4.9832 | 13150 | 0.0185          | 0.9298   | 0.9288  | 0.0185 |


### Framework versions

- Transformers 4.47.0
- Pytorch 2.5.1+cu124
- Datasets 2.19.2
- Tokenizers 0.21.0