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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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metrics:
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- accuracy
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model-index:
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- name: mpnet-adaptation_mitigation-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-adaptation_mitigation-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: 0.2117
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- Precision Micro: 0.9175
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- Precision Weighted: 0.9181
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- Precision Samples: 0.9256
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- Recall Micro: 0.9281
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- Recall Weighted: 0.9281
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- Recall Samples: 0.9314
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- F1-score: 0.9263
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- Accuracy: 0.9082
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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: 8e-05
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- train_batch_size: 8
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- eval_batch_size: 8
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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: 1
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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 | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:---------------:|:------------------:|:-----------------:|:------------:|:---------------:|:--------------:|:--------:|:--------:|
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| 0.3291 | 1.0 | 1051 | 0.2117 | 0.9175 | 0.9181 | 0.9256 | 0.9281 | 0.9281 | 0.9314 | 0.9263 | 0.9082 |
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### Framework versions
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- Transformers 4.28.1
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- Pytorch 2.0.0+cu118
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- Datasets 2.11.0
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- Tokenizers 0.13.3
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