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update model card README.md
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README.md
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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: ikitracs_conditional
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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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# ikitracs_conditional
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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: 0.9018
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- Precision Weighted: 0.7669
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- Precision Macro: 0.7479
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- Recall Weighted: 0.7712
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- Recall Samples: 0.7345
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- F1-score: 0.7400
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- Accuracy: 0.7712
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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: 5.8e-05
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- train_batch_size: 8
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- eval_batch_size: 3
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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: 300
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- num_epochs: 5
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Precision Weighted | Precision Macro | Recall Weighted | Recall Samples | F1-score | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:------------------:|:---------------:|:---------------:|:--------------:|:--------:|:--------:|
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| 0.6787 | 1.0 | 212 | 0.6461 | 0.6859 | 0.6493 | 0.6792 | 0.6546 | 0.6513 | 0.6792 |
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| 0.6006 | 2.0 | 424 | 0.6125 | 0.7370 | 0.7301 | 0.7429 | 0.6690 | 0.6792 | 0.7429 |
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| 0.4826 | 3.0 | 636 | 0.7111 | 0.7458 | 0.7270 | 0.7524 | 0.7071 | 0.7142 | 0.7524 |
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| 0.3487 | 4.0 | 848 | 0.7359 | 0.7536 | 0.7242 | 0.75 | 0.7297 | 0.7266 | 0.75 |
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| 0.2199 | 5.0 | 1060 | 0.9018 | 0.7669 | 0.7479 | 0.7712 | 0.7345 | 0.7400 | 0.7712 |
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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 2.13.0
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- Tokenizers 0.13.3
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