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--- |
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library_name: transformers |
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license: mit |
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base_model: BAAI/bge-base-en-v1.5 |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: bge-base-en-v1.5-2024-12-28_14-02-19-quality-weight-0.6 |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# bge-base-en-v1.5-2024-12-28_14-02-19-quality-weight-0.6 |
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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. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0186 |
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- Spearman: 0.9302 |
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- Pearson: 0.9279 |
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- Mse: 0.0186 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-05 |
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- train_batch_size: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- gradient_accumulation_steps: 64 |
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- total_train_batch_size: 256 |
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_ratio: 0.05 |
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- num_epochs: 5 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Spearman | Pearson | Mse | |
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|:-------------:|:------:|:-----:|:---------------:|:--------:|:-------:|:------:| |
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| 0.0375 | 0.0997 | 263 | 0.0382 | 0.8522 | 0.8465 | 0.0382 | |
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| 0.0365 | 0.1994 | 526 | 0.0339 | 0.8742 | 0.8658 | 0.0339 | |
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| 0.043 | 0.2990 | 789 | 0.0319 | 0.8810 | 0.8754 | 0.0319 | |
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| 0.0283 | 0.3987 | 1052 | 0.0322 | 0.8905 | 0.8817 | 0.0322 | |
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| 0.0319 | 0.4984 | 1315 | 0.0295 | 0.8962 | 0.8914 | 0.0295 | |
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| 0.02 | 0.5981 | 1578 | 0.0278 | 0.8984 | 0.8968 | 0.0278 | |
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| 0.0334 | 0.6978 | 1841 | 0.0246 | 0.9046 | 0.9025 | 0.0246 | |
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| 0.0272 | 0.7975 | 2104 | 0.0263 | 0.9070 | 0.9033 | 0.0263 | |
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| 0.0295 | 0.8971 | 2367 | 0.0235 | 0.9068 | 0.9067 | 0.0235 | |
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| 0.0208 | 0.9968 | 2630 | 0.0227 | 0.9103 | 0.9097 | 0.0227 | |
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| 0.0238 | 1.0963 | 2893 | 0.0241 | 0.9129 | 0.9105 | 0.0241 | |
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| 0.023 | 1.1960 | 3156 | 0.0226 | 0.9135 | 0.9117 | 0.0226 | |
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| 0.0168 | 1.2956 | 3419 | 0.0223 | 0.9164 | 0.9140 | 0.0223 | |
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| 0.0182 | 1.3953 | 3682 | 0.0213 | 0.9183 | 0.9162 | 0.0213 | |
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| 0.0189 | 1.4950 | 3945 | 0.0214 | 0.9185 | 0.9174 | 0.0214 | |
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| 0.018 | 1.5947 | 4208 | 0.0209 | 0.9183 | 0.9184 | 0.0209 | |
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| 0.0148 | 1.6944 | 4471 | 0.0209 | 0.9198 | 0.9188 | 0.0209 | |
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| 0.0137 | 1.7940 | 4734 | 0.0204 | 0.9210 | 0.9210 | 0.0204 | |
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| 0.021 | 1.8937 | 4997 | 0.0204 | 0.9205 | 0.9208 | 0.0204 | |
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| 0.0212 | 1.9934 | 5260 | 0.0204 | 0.9227 | 0.9226 | 0.0204 | |
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| 0.0099 | 2.0929 | 5523 | 0.0198 | 0.9235 | 0.9229 | 0.0198 | |
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| 0.0128 | 2.1925 | 5786 | 0.0199 | 0.9231 | 0.9224 | 0.0199 | |
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| 0.0116 | 2.2922 | 6049 | 0.0198 | 0.9244 | 0.9219 | 0.0198 | |
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| 0.0145 | 2.3919 | 6312 | 0.0200 | 0.9226 | 0.9222 | 0.0200 | |
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| 0.0157 | 2.4916 | 6575 | 0.0204 | 0.9249 | 0.9235 | 0.0204 | |
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| 0.0104 | 2.5913 | 6838 | 0.0196 | 0.9253 | 0.9248 | 0.0196 | |
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| 0.0118 | 2.6910 | 7101 | 0.0194 | 0.9243 | 0.9245 | 0.0194 | |
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| 0.0108 | 2.7906 | 7364 | 0.0193 | 0.9267 | 0.9265 | 0.0193 | |
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| 0.0171 | 2.8903 | 7627 | 0.0188 | 0.9259 | 0.9268 | 0.0188 | |
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| 0.0087 | 2.9900 | 7890 | 0.0190 | 0.9275 | 0.9272 | 0.0190 | |
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| 0.0093 | 3.0894 | 8153 | 0.0188 | 0.9277 | 0.9271 | 0.0188 | |
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| 0.01 | 3.1891 | 8416 | 0.0190 | 0.9279 | 0.9268 | 0.0190 | |
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| 0.0117 | 3.2888 | 8679 | 0.0186 | 0.9277 | 0.9273 | 0.0186 | |
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| 0.0143 | 3.3885 | 8942 | 0.0189 | 0.9281 | 0.9273 | 0.0189 | |
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| 0.0088 | 3.4882 | 9205 | 0.0187 | 0.9284 | 0.9280 | 0.0187 | |
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| 0.008 | 3.5879 | 9468 | 0.0191 | 0.9288 | 0.9278 | 0.0191 | |
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| 0.0102 | 3.6875 | 9731 | 0.0185 | 0.9290 | 0.9285 | 0.0185 | |
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| 0.0079 | 3.7872 | 9994 | 0.0186 | 0.9291 | 0.9282 | 0.0186 | |
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| 0.0105 | 3.8869 | 10257 | 0.0184 | 0.9290 | 0.9282 | 0.0184 | |
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| 0.0138 | 3.9866 | 10520 | 0.0185 | 0.9294 | 0.9285 | 0.0185 | |
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| 0.0078 | 4.0860 | 10783 | 0.0187 | 0.9293 | 0.9285 | 0.0187 | |
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| 0.0064 | 4.1857 | 11046 | 0.0185 | 0.9296 | 0.9287 | 0.0185 | |
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| 0.008 | 4.2854 | 11309 | 0.0186 | 0.9293 | 0.9284 | 0.0186 | |
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| 0.0081 | 4.3851 | 11572 | 0.0184 | 0.9297 | 0.9288 | 0.0184 | |
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| 0.007 | 4.4848 | 11835 | 0.0185 | 0.9297 | 0.9287 | 0.0185 | |
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| 0.0075 | 4.5845 | 12098 | 0.0185 | 0.9299 | 0.9290 | 0.0185 | |
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| 0.0072 | 4.6841 | 12361 | 0.0186 | 0.9298 | 0.9287 | 0.0186 | |
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| 0.0067 | 4.7838 | 12624 | 0.0185 | 0.9298 | 0.9287 | 0.0185 | |
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| 0.0084 | 4.8835 | 12887 | 0.0185 | 0.9298 | 0.9288 | 0.0185 | |
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| 0.007 | 4.9832 | 13150 | 0.0185 | 0.9298 | 0.9288 | 0.0185 | |
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### Framework versions |
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- Transformers 4.47.0 |
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- Pytorch 2.5.1+cu124 |
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- Datasets 2.19.2 |
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- Tokenizers 0.21.0 |
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