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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-large-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-large-en-v1.5-2024-12-10_07-12-15-quality-weight-1 |
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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-large-en-v1.5-2024-12-10_07-12-15-quality-weight-1 |
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This model is a fine-tuned version of [BAAI/bge-large-en-v1.5](https://huggingface.co/BAAI/bge-large-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: 0.0151 |
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- Spearman: 0.9383 |
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- Pearson: 0.9340 |
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- Mse: 0.0151 |
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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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| 0.0301 | 0.0997 | 263 | 0.0276 | 0.8847 | 0.8733 | 0.0276 | |
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| 0.0296 | 0.1994 | 526 | 0.0279 | 0.8977 | 0.8830 | 0.0279 | |
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| 0.0314 | 0.2990 | 789 | 0.0236 | 0.9045 | 0.8946 | 0.0236 | |
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| 0.0228 | 0.3987 | 1052 | 0.0231 | 0.9065 | 0.8942 | 0.0231 | |
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| 0.0241 | 0.4984 | 1315 | 0.0217 | 0.9111 | 0.9031 | 0.0217 | |
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| 0.0162 | 0.5981 | 1578 | 0.0221 | 0.9114 | 0.9033 | 0.0221 | |
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| 0.0227 | 0.6978 | 1841 | 0.0203 | 0.9168 | 0.9101 | 0.0203 | |
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| 0.0203 | 0.7975 | 2104 | 0.0211 | 0.9181 | 0.9105 | 0.0211 | |
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| 0.0215 | 0.8971 | 2367 | 0.0199 | 0.9155 | 0.9102 | 0.0199 | |
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| 0.0203 | 0.9968 | 2630 | 0.0193 | 0.9204 | 0.9151 | 0.0193 | |
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| 0.0187 | 1.0963 | 2893 | 0.0188 | 0.9234 | 0.9151 | 0.0188 | |
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| 0.0192 | 1.1960 | 3156 | 0.0185 | 0.9240 | 0.9186 | 0.0185 | |
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| 0.0128 | 1.2956 | 3419 | 0.0195 | 0.9241 | 0.9177 | 0.0195 | |
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| 0.0128 | 1.3953 | 3682 | 0.0175 | 0.9261 | 0.9213 | 0.0175 | |
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| 0.0191 | 1.4950 | 3945 | 0.0177 | 0.9256 | 0.9206 | 0.0177 | |
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| 0.0129 | 1.5947 | 4208 | 0.0186 | 0.9246 | 0.9199 | 0.0186 | |
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| 0.0167 | 1.6944 | 4471 | 0.0179 | 0.9272 | 0.9223 | 0.0179 | |
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| 0.0098 | 1.7940 | 4734 | 0.0177 | 0.9282 | 0.9249 | 0.0177 | |
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| 0.0155 | 1.8937 | 4997 | 0.0173 | 0.9275 | 0.9239 | 0.0173 | |
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| 0.0153 | 1.9934 | 5260 | 0.0181 | 0.9300 | 0.9261 | 0.0181 | |
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| 0.0107 | 2.0929 | 5523 | 0.0167 | 0.9311 | 0.9267 | 0.0167 | |
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| 0.0126 | 2.1925 | 5786 | 0.0164 | 0.9306 | 0.9264 | 0.0164 | |
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| 0.0096 | 2.2922 | 6049 | 0.0164 | 0.9318 | 0.9273 | 0.0164 | |
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| 0.012 | 2.3919 | 6312 | 0.0162 | 0.9311 | 0.9279 | 0.0162 | |
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| 0.0126 | 2.4916 | 6575 | 0.0170 | 0.9329 | 0.9285 | 0.0170 | |
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| 0.0086 | 2.5913 | 6838 | 0.0166 | 0.9323 | 0.9283 | 0.0166 | |
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| 0.0088 | 2.6910 | 7101 | 0.0160 | 0.9334 | 0.9295 | 0.0160 | |
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| 0.0088 | 2.7906 | 7364 | 0.0158 | 0.9339 | 0.9302 | 0.0158 | |
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| 0.013 | 2.8903 | 7627 | 0.0158 | 0.9336 | 0.9299 | 0.0158 | |
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| 0.0073 | 2.9900 | 7890 | 0.0157 | 0.9346 | 0.9308 | 0.0157 | |
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| 0.0071 | 3.0894 | 8153 | 0.0155 | 0.9354 | 0.9317 | 0.0155 | |
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| 0.0081 | 3.1891 | 8416 | 0.0158 | 0.9360 | 0.9317 | 0.0158 | |
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| 0.0092 | 3.2888 | 8679 | 0.0155 | 0.9358 | 0.9316 | 0.0155 | |
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| 0.0088 | 3.3885 | 8942 | 0.0156 | 0.9361 | 0.9324 | 0.0156 | |
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| 0.0058 | 3.4882 | 9205 | 0.0153 | 0.9366 | 0.9329 | 0.0153 | |
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| 0.0061 | 3.5879 | 9468 | 0.0158 | 0.9367 | 0.9322 | 0.0158 | |
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| 0.0081 | 3.6875 | 9731 | 0.0154 | 0.9369 | 0.9333 | 0.0154 | |
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| 0.0053 | 3.7872 | 9994 | 0.0150 | 0.9369 | 0.9336 | 0.0150 | |
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| 0.0063 | 3.8869 | 10257 | 0.0149 | 0.9373 | 0.9341 | 0.0149 | |
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| 0.006 | 3.9866 | 10520 | 0.0152 | 0.9375 | 0.9341 | 0.0152 | |
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| 0.0046 | 4.0860 | 10783 | 0.0150 | 0.9376 | 0.9345 | 0.0150 | |
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| 0.0044 | 4.1857 | 11046 | 0.0150 | 0.9376 | 0.9343 | 0.0150 | |
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| 0.0051 | 4.2854 | 11309 | 0.0151 | 0.9377 | 0.9343 | 0.0151 | |
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| 0.0062 | 4.3851 | 11572 | 0.0150 | 0.9378 | 0.9346 | 0.0150 | |
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| 0.0044 | 4.4848 | 11835 | 0.0150 | 0.9380 | 0.9346 | 0.0150 | |
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| 0.0052 | 4.5845 | 12098 | 0.0150 | 0.9378 | 0.9346 | 0.0150 | |
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| 0.0037 | 4.6841 | 12361 | 0.0151 | 0.9378 | 0.9345 | 0.0151 | |
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| 0.0031 | 4.7838 | 12624 | 0.0151 | 0.9378 | 0.9346 | 0.0151 | |
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| 0.0053 | 4.8835 | 12887 | 0.0150 | 0.9379 | 0.9346 | 0.0150 | |
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| 0.0046 | 4.9832 | 13150 | 0.0150 | 0.9379 | 0.9346 | 0.0150 | |
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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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