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---
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
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