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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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- precision |
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- recall |
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base_model: facebook/bart-base |
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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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<!-- 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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# bart-base-lora |
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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: 0.6655 |
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- Accuracy: 0.7963 |
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- Precision: 0.7841 |
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- Recall: 0.7963 |
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- Precision Macro: 0.5968 |
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- Recall Macro: 0.6325 |
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- Macro Fpr: 0.0186 |
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- Weighted Fpr: 0.0179 |
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- Weighted Specificity: 0.9749 |
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- Macro Specificity: 0.9847 |
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- Weighted Sensitivity: 0.7963 |
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- Macro Sensitivity: 0.6325 |
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- F1 Micro: 0.7963 |
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- F1 Macro: 0.6074 |
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- F1 Weighted: 0.7859 |
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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: 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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### Training results |
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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 | 1.2642 | 0.6313 | 0.5477 | 0.6313 | 0.3009 | 0.3127 | 0.0428 | 0.0400 | 0.9351 | 0.9711 | 0.6313 | 0.3127 | 0.6313 | 0.2941 | 0.5769 | |
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| No log | 2.0 | 321 | 0.8962 | 0.7119 | 0.6939 | 0.7119 | 0.3937 | 0.4525 | 0.0285 | 0.0281 | 0.9669 | 0.9786 | 0.7119 | 0.4525 | 0.7119 | 0.4107 | 0.6960 | |
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| No log | 3.0 | 482 | 0.8204 | 0.7196 | 0.6953 | 0.7196 | 0.3974 | 0.4468 | 0.0278 | 0.0271 | 0.9653 | 0.9790 | 0.7196 | 0.4468 | 0.7196 | 0.3998 | 0.6885 | |
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| 1.2731 | 4.0 | 643 | 0.7519 | 0.7436 | 0.7186 | 0.7436 | 0.4131 | 0.4673 | 0.0244 | 0.0240 | 0.9695 | 0.9809 | 0.7436 | 0.4673 | 0.7436 | 0.4272 | 0.7248 | |
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| 1.2731 | 5.0 | 803 | 0.7364 | 0.7475 | 0.7524 | 0.7475 | 0.6132 | 0.5050 | 0.0243 | 0.0236 | 0.9679 | 0.9810 | 0.7475 | 0.5050 | 0.7475 | 0.4905 | 0.7286 | |
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| 1.2731 | 6.0 | 964 | 0.7273 | 0.7514 | 0.7423 | 0.7514 | 0.5784 | 0.5258 | 0.0237 | 0.0231 | 0.9699 | 0.9814 | 0.7514 | 0.5258 | 0.7514 | 0.5150 | 0.7311 | |
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| 0.7243 | 7.0 | 1125 | 0.6993 | 0.7645 | 0.7478 | 0.7645 | 0.5498 | 0.5565 | 0.0222 | 0.0215 | 0.9721 | 0.9824 | 0.7645 | 0.5565 | 0.7645 | 0.5453 | 0.7538 | |
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| 0.7243 | 8.0 | 1286 | 0.6952 | 0.7769 | 0.7639 | 0.7769 | 0.5682 | 0.5888 | 0.0207 | 0.0201 | 0.9731 | 0.9833 | 0.7769 | 0.5888 | 0.7769 | 0.5700 | 0.7649 | |
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| 0.7243 | 9.0 | 1446 | 0.6759 | 0.7823 | 0.7708 | 0.7823 | 0.5764 | 0.5877 | 0.0201 | 0.0195 | 0.9739 | 0.9838 | 0.7823 | 0.5877 | 0.7823 | 0.5699 | 0.7697 | |
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| 0.6098 | 10.0 | 1607 | 0.6705 | 0.7847 | 0.7720 | 0.7847 | 0.5899 | 0.6176 | 0.0199 | 0.0192 | 0.9732 | 0.9839 | 0.7847 | 0.6176 | 0.7847 | 0.5935 | 0.7724 | |
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| 0.6098 | 11.0 | 1768 | 0.6794 | 0.7909 | 0.7737 | 0.7909 | 0.5882 | 0.6237 | 0.0193 | 0.0185 | 0.9736 | 0.9843 | 0.7909 | 0.6237 | 0.7909 | 0.5988 | 0.7773 | |
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| 0.6098 | 12.0 | 1929 | 0.6836 | 0.7909 | 0.7816 | 0.7909 | 0.5973 | 0.6285 | 0.0192 | 0.0185 | 0.9742 | 0.9843 | 0.7909 | 0.6285 | 0.7909 | 0.6034 | 0.7802 | |
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| 0.5239 | 13.0 | 2089 | 0.6508 | 0.7932 | 0.7783 | 0.7932 | 0.5965 | 0.6273 | 0.0189 | 0.0183 | 0.9738 | 0.9845 | 0.7932 | 0.6273 | 0.7932 | 0.6046 | 0.7821 | |
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| 0.5239 | 14.0 | 2250 | 0.6588 | 0.7963 | 0.7823 | 0.7963 | 0.5957 | 0.6290 | 0.0186 | 0.0179 | 0.9746 | 0.9847 | 0.7963 | 0.6290 | 0.7963 | 0.6055 | 0.7852 | |
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| 0.5239 | 14.93 | 2400 | 0.6655 | 0.7963 | 0.7841 | 0.7963 | 0.5968 | 0.6325 | 0.0186 | 0.0179 | 0.9749 | 0.9847 | 0.7963 | 0.6325 | 0.7963 | 0.6074 | 0.7859 | |
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### Framework versions |
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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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