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--- |
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tags: |
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- generated_from_trainer |
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base_model: sentence-transformers/multi-qa-MiniLM-L6-cos-v1 |
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metrics: |
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- accuracy |
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- precision |
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- recall |
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- f1 |
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model-index: |
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- name: all_keywords_multi-qa-MiniLM-L6-cos-v1_another |
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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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# all_keywords_multi-qa-MiniLM-L6-cos-v1_another |
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This model is a fine-tuned version of [sentence-transformers/multi-qa-MiniLM-L6-cos-v1](https://huggingface.co/sentence-transformers/multi-qa-MiniLM-L6-cos-v1) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.7780 |
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- Accuracy: 0.5526 |
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- Precision: 0.5526 |
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- Recall: 0.5526 |
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- F1: 0.5526 |
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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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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 15 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:| |
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| 2.3017 | 1.0 | 712 | 2.0180 | 0.4362 | |
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| 2.09 | 2.0 | 1424 | 1.8306 | 0.4390 | |
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| 1.775 | 3.0 | 2136 | 1.7843 | 0.4783 | |
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| 1.5811 | 4.0 | 2848 | 1.7686 | 0.5175 | |
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| 1.2665 | 5.0 | 3560 | 1.7257 | 0.5147 | |
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| 1.0957 | 6.0 | 4272 | 1.8126 | 0.5568 | |
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| 0.9661 | 7.0 | 4984 | 2.0472 | 0.5386 | |
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| 0.7399 | 8.0 | 5696 | 2.1375 | 0.5428 | |
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| 0.6533 | 9.0 | 6408 | 2.2761 | 0.5400 | |
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| 0.5268 | 10.0 | 7120 | 2.4777 | 0.5400 | |
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| 0.5067 | 11.0 | 7832 | 2.6160 | 0.5372 | |
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| 0.4209 | 12.0 | 8544 | 2.6253 | 0.5512 | |
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| 0.4102 | 13.0 | 9256 | 2.7287 | 0.5442 | |
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| 0.3405 | 14.0 | 9968 | 2.7607 | 0.5470 | |
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| 0.3278 | 15.0 | 10680 | 2.7780 | 0.5526 | |
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### Framework versions |
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- Transformers 4.39.3 |
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- Pytorch 2.2.1+cu118 |
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- Datasets 2.14.7 |
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- Tokenizers 0.15.2 |
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