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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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model-index: |
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- name: pubmed-mixed-noise-v3-0.1 |
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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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# pubmed-mixed-noise-v3-0.1 |
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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: 0.2607 |
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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: 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: 10 |
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- num_epochs: 3 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:-----:|:---------------:| |
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| 0.5222 | 0.11 | 500 | 0.4206 | |
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| 0.3862 | 0.21 | 1000 | 0.3907 | |
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| 0.4108 | 0.32 | 1500 | 0.3568 | |
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| 0.3871 | 0.43 | 2000 | 0.3415 | |
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| 0.3846 | 0.54 | 2500 | 0.3240 | |
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| 0.3313 | 0.64 | 3000 | 0.3124 | |
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| 0.3317 | 0.75 | 3500 | 0.3066 | |
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| 0.3136 | 0.86 | 4000 | 0.3049 | |
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| 0.3267 | 0.96 | 4500 | 0.2925 | |
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| 0.2816 | 1.07 | 5000 | 0.2929 | |
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| 0.2421 | 1.18 | 5500 | 0.2882 | |
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| 0.2643 | 1.28 | 6000 | 0.2872 | |
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| 0.2776 | 1.39 | 6500 | 0.2824 | |
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| 0.2854 | 1.5 | 7000 | 0.2751 | |
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| 0.2301 | 1.61 | 7500 | 0.2756 | |
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| 0.2118 | 1.71 | 8000 | 0.2770 | |
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| 0.2079 | 1.82 | 8500 | 0.2732 | |
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| 0.2474 | 1.93 | 9000 | 0.2631 | |
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| 0.1482 | 2.03 | 9500 | 0.2693 | |
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| 0.1908 | 2.14 | 10000 | 0.2656 | |
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| 0.2017 | 2.25 | 10500 | 0.2647 | |
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| 0.1687 | 2.35 | 11000 | 0.2680 | |
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| 0.191 | 2.46 | 11500 | 0.2630 | |
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| 0.1821 | 2.57 | 12000 | 0.2618 | |
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| 0.2301 | 2.68 | 12500 | 0.2605 | |
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| 0.2106 | 2.78 | 13000 | 0.2601 | |
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| 0.1637 | 2.89 | 13500 | 0.2617 | |
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| 0.1902 | 3.0 | 14000 | 0.2607 | |
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### Framework versions |
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- Transformers 4.36.1 |
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- Pytorch 2.0.1 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.0 |
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