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bart-large-lora

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README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: facebook/bart-base
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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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+ - precision
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+ - recall
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+ model-index:
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+ - name: bart-base-lora
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+ results: []
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+ ---
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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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+
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+ # bart-base-lora
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+
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+ This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co/facebook/bart-base) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.6647
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+ - Accuracy: 0.7901
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+ - Precision: 0.7852
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+ - Recall: 0.7901
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+ - Precision Macro: 0.6664
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+ - Recall Macro: 0.6485
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+ - Macro Fpr: 0.0194
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+ - Weighted Fpr: 0.0186
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+ - Weighted Specificity: 0.9735
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+ - Macro Specificity: 0.9842
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+ - Weighted Sensitivity: 0.7901
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+ - Macro Sensitivity: 0.6485
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+ - F1 Micro: 0.7901
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+ - F1 Macro: 0.6250
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+ - F1 Weighted: 0.7804
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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: 8
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+ - eval_batch_size: 8
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+ - seed: 42
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+ - gradient_accumulation_steps: 4
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+ - total_train_batch_size: 32
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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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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | Precision Macro | Recall Macro | Macro Fpr | Weighted Fpr | Weighted Specificity | Macro Specificity | Weighted Sensitivity | Macro Sensitivity | F1 Micro | F1 Macro | F1 Weighted |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:---------------:|:------------:|:---------:|:------------:|:--------------------:|:-----------------:|:--------------------:|:-----------------:|:--------:|:--------:|:-----------:|
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+ | No log | 1.0 | 160 | 1.3205 | 0.6112 | 0.5322 | 0.6112 | 0.2887 | 0.3024 | 0.0464 | 0.0435 | 0.9266 | 0.9692 | 0.6112 | 0.3024 | 0.6112 | 0.2871 | 0.5575 |
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+ | No log | 2.0 | 321 | 0.8875 | 0.6995 | 0.6728 | 0.6995 | 0.3822 | 0.4254 | 0.0306 | 0.0298 | 0.9609 | 0.9774 | 0.6995 | 0.4254 | 0.6995 | 0.3948 | 0.6808 |
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+ | No log | 3.0 | 482 | 0.8427 | 0.7064 | 0.6952 | 0.7064 | 0.4131 | 0.4442 | 0.0295 | 0.0288 | 0.9641 | 0.9780 | 0.7064 | 0.4442 | 0.7064 | 0.3969 | 0.6752 |
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+ | 1.2895 | 4.0 | 643 | 0.7719 | 0.7273 | 0.7132 | 0.7273 | 0.4198 | 0.4598 | 0.0264 | 0.0261 | 0.9690 | 0.9798 | 0.7273 | 0.4598 | 0.7273 | 0.4284 | 0.7167 |
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+ | 1.2895 | 5.0 | 803 | 0.7388 | 0.7506 | 0.7400 | 0.7506 | 0.5733 | 0.5165 | 0.0239 | 0.0232 | 0.9697 | 0.9814 | 0.7506 | 0.5165 | 0.7506 | 0.5072 | 0.7368 |
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+ | 1.2895 | 6.0 | 964 | 0.7526 | 0.7444 | 0.7337 | 0.7444 | 0.5703 | 0.5230 | 0.0247 | 0.0239 | 0.9691 | 0.9809 | 0.7444 | 0.5230 | 0.7444 | 0.5088 | 0.7268 |
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+ | 0.7332 | 7.0 | 1125 | 0.7082 | 0.7552 | 0.7436 | 0.7552 | 0.5665 | 0.5728 | 0.0233 | 0.0226 | 0.9712 | 0.9818 | 0.7552 | 0.5728 | 0.7552 | 0.5609 | 0.7461 |
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+ | 0.7332 | 8.0 | 1286 | 0.7161 | 0.7583 | 0.7489 | 0.7583 | 0.5641 | 0.5975 | 0.0228 | 0.0223 | 0.9721 | 0.9820 | 0.7583 | 0.5975 | 0.7583 | 0.5756 | 0.7503 |
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+ | 0.7332 | 9.0 | 1446 | 0.6831 | 0.7777 | 0.7587 | 0.7777 | 0.5781 | 0.6069 | 0.0208 | 0.0200 | 0.9715 | 0.9833 | 0.7777 | 0.6069 | 0.7777 | 0.5875 | 0.7653 |
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+ | 0.6167 | 10.0 | 1607 | 0.6683 | 0.7862 | 0.7714 | 0.7862 | 0.5917 | 0.6174 | 0.0198 | 0.0191 | 0.9728 | 0.9839 | 0.7862 | 0.6174 | 0.7862 | 0.5987 | 0.7754 |
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+ | 0.6167 | 11.0 | 1768 | 0.6885 | 0.7761 | 0.7628 | 0.7761 | 0.5817 | 0.6220 | 0.0210 | 0.0202 | 0.9723 | 0.9832 | 0.7761 | 0.6220 | 0.7761 | 0.5946 | 0.7642 |
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+ | 0.6167 | 12.0 | 1929 | 0.6830 | 0.7870 | 0.7826 | 0.7870 | 0.6627 | 0.6464 | 0.0197 | 0.0190 | 0.9734 | 0.9840 | 0.7870 | 0.6464 | 0.7870 | 0.6214 | 0.7764 |
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+ | 0.5314 | 13.0 | 2089 | 0.6605 | 0.7916 | 0.7770 | 0.7916 | 0.5965 | 0.6358 | 0.0192 | 0.0185 | 0.9741 | 0.9844 | 0.7916 | 0.6358 | 0.7916 | 0.6111 | 0.7818 |
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+ | 0.5314 | 14.0 | 2250 | 0.6614 | 0.7909 | 0.7794 | 0.7909 | 0.6368 | 0.6478 | 0.0193 | 0.0185 | 0.9729 | 0.9842 | 0.7909 | 0.6478 | 0.7909 | 0.6261 | 0.7803 |
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+ | 0.5314 | 14.93 | 2400 | 0.6647 | 0.7901 | 0.7852 | 0.7901 | 0.6664 | 0.6485 | 0.0194 | 0.0186 | 0.9735 | 0.9842 | 0.7901 | 0.6485 | 0.7901 | 0.6250 | 0.7804 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.35.2
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+ - Pytorch 2.1.0+cu121
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+ - Datasets 2.18.0
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+ - Tokenizers 0.15.1
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