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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-abs-noise-04 |
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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-abs-noise-04 |
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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: 0.5519 |
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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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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:-----:|:---------------:| |
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| 0.9533 | 0.11 | 500 | 0.7930 | |
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| 0.8667 | 0.21 | 1000 | 0.7234 | |
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| 0.797 | 0.32 | 1500 | 0.6901 | |
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| 0.7887 | 0.43 | 2000 | 0.6696 | |
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| 0.7616 | 0.54 | 2500 | 0.6600 | |
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| 0.6708 | 0.64 | 3000 | 0.6435 | |
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| 0.6794 | 0.75 | 3500 | 0.6287 | |
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| 0.6342 | 0.86 | 4000 | 0.6163 | |
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| 0.6815 | 0.96 | 4500 | 0.6073 | |
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| 0.6312 | 1.07 | 5000 | 0.6038 | |
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| 0.5506 | 1.18 | 5500 | 0.5975 | |
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| 0.5828 | 1.28 | 6000 | 0.5972 | |
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| 0.5568 | 1.39 | 6500 | 0.5920 | |
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| 0.5834 | 1.5 | 7000 | 0.5809 | |
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| 0.5236 | 1.61 | 7500 | 0.5808 | |
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| 0.5446 | 1.71 | 8000 | 0.5727 | |
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| 0.5838 | 1.82 | 8500 | 0.5691 | |
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| 0.5038 | 1.93 | 9000 | 0.5628 | |
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| 0.469 | 2.03 | 9500 | 0.5687 | |
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| 0.4529 | 2.14 | 10000 | 0.5673 | |
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| 0.4987 | 2.25 | 10500 | 0.5614 | |
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| 0.4471 | 2.35 | 11000 | 0.5621 | |
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| 0.4831 | 2.46 | 11500 | 0.5569 | |
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| 0.4683 | 2.57 | 12000 | 0.5565 | |
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| 0.4547 | 2.68 | 12500 | 0.5562 | |
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| 0.4346 | 2.78 | 13000 | 0.5543 | |
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| 0.47 | 2.89 | 13500 | 0.5534 | |
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| 0.4144 | 3.0 | 14000 | 0.5519 | |
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### Framework versions |
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- Transformers 4.34.1 |
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- Pytorch 2.1.0 |
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- Datasets 2.14.7 |
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- Tokenizers 0.14.1 |
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