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---
library_name: transformers
license: mit
base_model: BAAI/bge-base-en-v1.5
tags:
- generated_from_trainer
model-index:
- name: bge-base-en-v1.5-2024-12-05_13-34-00
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-v1.5-2024-12-05_13-34-00
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: 0.0228
- Spearman: 0.9285
- Pearson: 0.9285
- Mse: 0.0228
## 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: 32
- eval_batch_size: 32
- seed: 42
- 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 |
|:-------------:|:------:|:------:|:---------------:|:--------:|:-------:|:------:|
| 0.0525 | 0.1000 | 2110 | 0.0402 | 0.8683 | 0.8725 | 0.0402 |
| 0.0351 | 0.1999 | 4220 | 0.0424 | 0.8824 | 0.8816 | 0.0424 |
| 0.0314 | 0.2999 | 6330 | 0.0355 | 0.8829 | 0.8860 | 0.0355 |
| 0.038 | 0.3999 | 8440 | 0.0339 | 0.8940 | 0.8932 | 0.0339 |
| 0.0287 | 0.4998 | 10550 | 0.0318 | 0.8959 | 0.8982 | 0.0318 |
| 0.027 | 0.5998 | 12660 | 0.0308 | 0.8986 | 0.9010 | 0.0308 |
| 0.0376 | 0.6998 | 14770 | 0.0309 | 0.9019 | 0.9038 | 0.0309 |
| 0.0264 | 0.7997 | 16880 | 0.0301 | 0.9017 | 0.9049 | 0.0301 |
| 0.0311 | 0.8997 | 18990 | 0.0294 | 0.9030 | 0.9070 | 0.0294 |
| 0.0303 | 0.9997 | 21100 | 0.0286 | 0.9052 | 0.9085 | 0.0286 |
| 0.0252 | 1.0996 | 23210 | 0.0290 | 0.9085 | 0.9093 | 0.0290 |
| 0.0312 | 1.1996 | 25320 | 0.0287 | 0.9084 | 0.9093 | 0.0287 |
| 0.0238 | 1.2996 | 27430 | 0.0277 | 0.9095 | 0.9132 | 0.0277 |
| 0.0326 | 1.3995 | 29540 | 0.0295 | 0.9089 | 0.9096 | 0.0295 |
| 0.0204 | 1.4995 | 31650 | 0.0272 | 0.9104 | 0.9132 | 0.0272 |
| 0.0237 | 1.5995 | 33760 | 0.0304 | 0.9120 | 0.9099 | 0.0304 |
| 0.0285 | 1.6994 | 35870 | 0.0263 | 0.9128 | 0.9168 | 0.0263 |
| 0.0218 | 1.7994 | 37980 | 0.0262 | 0.9152 | 0.9185 | 0.0262 |
| 0.032 | 1.8994 | 40090 | 0.0259 | 0.9149 | 0.9186 | 0.0259 |
| 0.0211 | 1.9993 | 42200 | 0.0256 | 0.9155 | 0.9197 | 0.0256 |
| 0.0209 | 2.0993 | 44310 | 0.0253 | 0.9174 | 0.9190 | 0.0253 |
| 0.016 | 2.1993 | 46420 | 0.0259 | 0.9180 | 0.9194 | 0.0259 |
| 0.0122 | 2.2992 | 48530 | 0.0257 | 0.9181 | 0.9211 | 0.0257 |
| 0.0147 | 2.3992 | 50640 | 0.0276 | 0.9205 | 0.9210 | 0.0276 |
| 0.015 | 2.4992 | 52750 | 0.0253 | 0.9196 | 0.9223 | 0.0253 |
| 0.0201 | 2.5991 | 54860 | 0.0243 | 0.9208 | 0.9238 | 0.0243 |
| 0.0137 | 2.6991 | 56970 | 0.0243 | 0.9214 | 0.9232 | 0.0243 |
| 0.0158 | 2.7991 | 59080 | 0.0239 | 0.9224 | 0.9250 | 0.0239 |
| 0.018 | 2.8990 | 61190 | 0.0238 | 0.9234 | 0.9258 | 0.0238 |
| 0.0175 | 2.9990 | 63300 | 0.0234 | 0.9231 | 0.9264 | 0.0234 |
| 0.0122 | 3.0990 | 65410 | 0.0234 | 0.9241 | 0.9265 | 0.0234 |
| 0.0107 | 3.1989 | 67520 | 0.0238 | 0.9241 | 0.9264 | 0.0238 |
| 0.0081 | 3.2989 | 69630 | 0.0238 | 0.9248 | 0.9264 | 0.0238 |
| 0.0093 | 3.3989 | 71740 | 0.0233 | 0.9251 | 0.9270 | 0.0233 |
| 0.0128 | 3.4988 | 73850 | 0.0229 | 0.9258 | 0.9279 | 0.0229 |
| 0.0106 | 3.5988 | 75960 | 0.0231 | 0.9260 | 0.9281 | 0.0231 |
| 0.0134 | 3.6988 | 78070 | 0.0230 | 0.9261 | 0.9284 | 0.0230 |
| 0.0087 | 3.7987 | 80180 | 0.0227 | 0.9269 | 0.9295 | 0.0227 |
| 0.0086 | 3.8987 | 82290 | 0.0228 | 0.9267 | 0.9290 | 0.0228 |
| 0.0101 | 3.9987 | 84400 | 0.0225 | 0.9271 | 0.9294 | 0.0225 |
| 0.0075 | 4.0986 | 86510 | 0.0227 | 0.9271 | 0.9290 | 0.0227 |
| 0.0086 | 4.1986 | 88620 | 0.0225 | 0.9273 | 0.9295 | 0.0225 |
| 0.0067 | 4.2986 | 90730 | 0.0227 | 0.9277 | 0.9293 | 0.0227 |
| 0.009 | 4.3985 | 92840 | 0.0224 | 0.9275 | 0.9297 | 0.0224 |
| 0.007 | 4.4985 | 94950 | 0.0225 | 0.9278 | 0.9297 | 0.0225 |
| 0.0066 | 4.5985 | 97060 | 0.0225 | 0.9280 | 0.9300 | 0.0225 |
| 0.0118 | 4.6984 | 99170 | 0.0225 | 0.9279 | 0.9298 | 0.0225 |
| 0.0071 | 4.7984 | 101280 | 0.0225 | 0.9279 | 0.9299 | 0.0225 |
| 0.0071 | 4.8984 | 103390 | 0.0225 | 0.9280 | 0.9299 | 0.0225 |
| 0.0087 | 4.9983 | 105500 | 0.0225 | 0.9280 | 0.9299 | 0.0225 |
### Framework versions
- Transformers 4.46.3
- Pytorch 2.4.1+cu121
- Datasets 2.19.2
- Tokenizers 0.20.3
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