|
--- |
|
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_08-41-16-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-small-en-v1.5-2024-12-08_08-41-16-quality-weight-0.6 |
|
|
|
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: 0.0190 |
|
- Spearman: 0.9298 |
|
- Pearson: 0.9273 |
|
- Mse: 0.0190 |
|
|
|
## 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 | |
|
|:-------------:|:------:|:-----:|:---------------:|:--------:|:-------:|:------:| |
|
| 0.0289 | 0.3998 | 1055 | 0.0255 | 0.9013 | 0.8986 | 0.0255 | |
|
| 0.0241 | 0.7997 | 2110 | 0.0229 | 0.9114 | 0.9096 | 0.0229 | |
|
| 0.0214 | 1.1995 | 3165 | 0.0223 | 0.9175 | 0.9158 | 0.0223 | |
|
| 0.0209 | 1.5994 | 4220 | 0.0201 | 0.9228 | 0.9210 | 0.0201 | |
|
| 0.0186 | 1.9992 | 5275 | 0.0201 | 0.9245 | 0.9235 | 0.0201 | |
|
| 0.0165 | 2.3991 | 6330 | 0.0196 | 0.9254 | 0.9254 | 0.0196 | |
|
| 0.0152 | 2.7989 | 7385 | 0.0188 | 0.9272 | 0.9270 | 0.0188 | |
|
| 0.0121 | 3.1988 | 8440 | 0.0192 | 0.9281 | 0.9263 | 0.0192 | |
|
| 0.0132 | 3.5986 | 9495 | 0.0187 | 0.9293 | 0.9283 | 0.0187 | |
|
| 0.0135 | 3.9985 | 10550 | 0.0187 | 0.9294 | 0.9286 | 0.0187 | |
|
| 0.0103 | 4.3983 | 11605 | 0.0189 | 0.9296 | 0.9285 | 0.0189 | |
|
| 0.0116 | 4.7982 | 12660 | 0.0189 | 0.9297 | 0.9286 | 0.0189 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.46.3 |
|
- Pytorch 2.4.1+cu121 |
|
- Datasets 2.19.2 |
|
- Tokenizers 0.20.3 |
|
|
