metadata
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_11-40-21-quality-weight-0.3
results: []
bge-small-en-v1.5-2024-12-07_11-40-21-quality-weight-0.3
This model is a fine-tuned version of BAAI/bge-small-en-v1.5 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0204
- Spearman: 0.9287
- Pearson: 0.9299
- Mse: 0.0204
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 |
|---|---|---|---|---|---|---|
| 0.0308 | 0.3998 | 1055 | 0.0270 | 0.9002 | 0.9029 | 0.0270 |
| 0.026 | 0.7997 | 2110 | 0.0243 | 0.9100 | 0.9139 | 0.0243 |
| 0.0226 | 1.1995 | 3165 | 0.0237 | 0.9153 | 0.9187 | 0.0237 |
| 0.0222 | 1.5994 | 4220 | 0.0214 | 0.9218 | 0.9243 | 0.0214 |
| 0.0202 | 1.9992 | 5275 | 0.0217 | 0.9228 | 0.9265 | 0.0217 |
| 0.0175 | 2.3991 | 6330 | 0.0209 | 0.9235 | 0.9282 | 0.0209 |
| 0.0163 | 2.7989 | 7385 | 0.0202 | 0.9258 | 0.9299 | 0.0202 |
| 0.0127 | 3.1988 | 8440 | 0.0204 | 0.9268 | 0.9291 | 0.0204 |
| 0.0137 | 3.5986 | 9495 | 0.0201 | 0.9279 | 0.9308 | 0.0201 |
| 0.0142 | 3.9985 | 10550 | 0.0199 | 0.9278 | 0.9310 | 0.0199 |
| 0.0106 | 4.3983 | 11605 | 0.0202 | 0.9280 | 0.9309 | 0.0202 |
| 0.012 | 4.7982 | 12660 | 0.0202 | 0.9282 | 0.9310 | 0.0202 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.4.1+cu121
- Datasets 2.19.2
- Tokenizers 0.20.3