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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: 3.6836
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- Accuracy: 0.5091
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- Precision: 0.5091
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- Recall: 0.5091
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- F1: 0.5091
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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: 20
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:|
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| 2.3001 | 1.0 | 712 | 1.9740 | 0.4306 | 0.4306 | 0.4306 | 0.4306 |
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| 2.0028 | 2.0 | 1424 | 1.9084 | 0.4418 | 0.4418 | 0.4418 | 0.4418 |
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| 1.7335 | 3.0 | 2136 | 1.8073 | 0.4642 | 0.4642 | 0.4642 | 0.4642 |
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| 1.6116 | 4.0 | 2848 | 1.8696 | 0.4853 | 0.4853 | 0.4853 | 0.4853 |
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| 1.2663 | 5.0 | 3560 | 1.8992 | 0.4783 | 0.4783 | 0.4783 | 0.4783 |
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| 1.0998 | 6.0 | 4272 | 2.0148 | 0.4923 | 0.4923 | 0.4923 | 0.4923 |
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| 1.0126 | 7.0 | 4984 | 2.3935 | 0.4684 | 0.4684 | 0.4684 | 0.4684 |
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| 0.7917 | 8.0 | 5696 | 2.5295 | 0.5035 | 0.5035 | 0.5035 | 0.5035 |
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| 0.7038 | 9.0 | 6408 | 2.9043 | 0.4909 | 0.4909 | 0.4909 | 0.4909 |
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| 0.601 | 10.0 | 7120 | 2.9520 | 0.5021 | 0.5021 | 0.5021 | 0.5021 |
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| 0.5927 | 11.0 | 7832 | 3.0934 | 0.5175 | 0.5175 | 0.5175 | 0.5175 |
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| 0.5112 | 12.0 | 8544 | 3.2217 | 0.5021 | 0.5021 | 0.5021 | 0.5021 |
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| 0.4325 | 13.0 | 9256 | 3.3412 | 0.5119 | 0.5119 | 0.5119 | 0.5119 |
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| 0.4005 | 14.0 | 9968 | 3.4485 | 0.5161 | 0.5161 | 0.5161 | 0.5161 |
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| 0.3646 | 15.0 | 10680 | 3.6021 | 0.4825 | 0.4825 | 0.4825 | 0.4825 |
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| 0.3385 | 16.0 | 11392 | 3.4522 | 0.5203 | 0.5203 | 0.5203 | 0.5203 |
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| 0.316 | 17.0 | 12104 | 3.5701 | 0.5175 | 0.5175 | 0.5175 | 0.5175 |
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| 0.266 | 18.0 | 12816 | 3.6202 | 0.5063 | 0.5063 | 0.5063 | 0.5063 |
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| 0.2518 | 19.0 | 13528 | 3.6250 | 0.5175 | 0.5175 | 0.5175 | 0.5175 |
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| 0.254 | 20.0 | 14240 | 3.6836 | 0.5091 | 0.5091 | 0.5091 | 0.5091 |
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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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