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---
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license: apache-2.0
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tags:
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- generated_from_trainer
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model-index:
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- name: mpnet-multilabel-sector-classifier
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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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# mpnet-multilabel-sector-classifier
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This model is a fine-tuned version of [sentence-transformers/all-mpnet-base-v2](https://huggingface.co/sentence-transformers/all-mpnet-base-v2) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.2273
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- Precision Micro: 0.8075
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- Precision Weighted: 0.8110
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- Precision Samples: 0.8365
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- Recall Micro: 0.8897
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- Recall Weighted: 0.8897
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- Recall Samples: 0.8922
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- F1-score: 0.8464
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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: 6.9e-05
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- train_batch_size: 16
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- eval_batch_size: 16
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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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- lr_scheduler_warmup_steps: 200
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- num_epochs: 8
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Precision Micro | Precision Weighted | Precision Samples | Recall Micro | Recall Weighted | Recall Samples | F1-score |
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|:-------------:|:-----:|:----:|:---------------:|:---------------:|:------------------:|:-----------------:|:------------:|:---------------:|:--------------:|:--------:|
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| 0.4478 | 1.0 | 897 | 0.2277 | 0.6731 | 0.7183 | 0.7460 | 0.8822 | 0.8822 | 0.8989 | 0.7871 |
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| 0.2241 | 2.0 | 1794 | 0.1862 | 0.7088 | 0.7485 | 0.7754 | 0.8933 | 0.8933 | 0.9110 | 0.8108 |
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| 0.1647 | 3.0 | 2691 | 0.2025 | 0.6785 | 0.7023 | 0.7634 | 0.9124 | 0.9124 | 0.9252 | 0.8077 |
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| 0.1232 | 4.0 | 3588 | 0.1839 | 0.7274 | 0.7322 | 0.7976 | 0.9029 | 0.9029 | 0.9134 | 0.8286 |
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| 0.0899 | 5.0 | 4485 | 0.1889 | 0.7919 | 0.8007 | 0.8350 | 0.8909 | 0.8909 | 0.9060 | 0.8483 |
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| 0.0653 | 6.0 | 5382 | 0.2039 | 0.7478 | 0.7544 | 0.8098 | 0.8973 | 0.8973 | 0.9114 | 0.8346 |
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| 0.0462 | 7.0 | 6279 | 0.2149 | 0.7447 | 0.7500 | 0.8060 | 0.8989 | 0.8989 | 0.9107 | 0.8323 |
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| 0.0336 | 8.0 | 7176 | 0.2181 | 0.7733 | 0.7780 | 0.8221 | 0.8909 | 0.8909 | 0.9031 | 0.8400 |
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### Framework versions
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- Transformers 4.28.0
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- Pytorch 2.0.1+cu118
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- Datasets 2.12.0
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- Tokenizers 0.13.3
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