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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-small-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-small-en-v1.5-2024-12-07_18-39-49-quality-weight-0.4 |
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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-small-en-v1.5-2024-12-07_18-39-49-quality-weight-0.4 |
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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. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0199 |
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- Spearman: 0.9293 |
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- Pearson: 0.9291 |
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- Mse: 0.0199 |
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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: 64 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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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 | 0.3998 | 1055 | 0.0265 | 0.9008 | 0.9017 | 0.0265 | |
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| 0.0253 | 0.7997 | 2110 | 0.0238 | 0.9108 | 0.9126 | 0.0238 | |
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| 0.0222 | 1.1995 | 3165 | 0.0231 | 0.9164 | 0.9179 | 0.0231 | |
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| 0.0217 | 1.5994 | 4220 | 0.0209 | 0.9222 | 0.9232 | 0.0209 | |
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| 0.0195 | 1.9992 | 5275 | 0.0211 | 0.9234 | 0.9254 | 0.0211 | |
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| 0.0171 | 2.3991 | 6330 | 0.0204 | 0.9244 | 0.9275 | 0.0204 | |
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| 0.0159 | 2.7989 | 7385 | 0.0197 | 0.9265 | 0.9291 | 0.0197 | |
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| 0.0124 | 3.1988 | 8440 | 0.0200 | 0.9274 | 0.9282 | 0.0200 | |
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| 0.0135 | 3.5986 | 9495 | 0.0196 | 0.9285 | 0.9301 | 0.0196 | |
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| 0.014 | 3.9985 | 10550 | 0.0194 | 0.9285 | 0.9304 | 0.0194 | |
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| 0.0103 | 4.3983 | 11605 | 0.0197 | 0.9287 | 0.9302 | 0.0197 | |
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| 0.0119 | 4.7982 | 12660 | 0.0197 | 0.9289 | 0.9303 | 0.0197 | |
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### Framework versions |
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- Transformers 4.46.3 |
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- Pytorch 2.4.1+cu121 |
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- Datasets 2.19.2 |
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- Tokenizers 0.20.3 |
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