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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-03 |
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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-03 |
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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: 0.4432 |
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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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| 0.7656 | 0.11 | 500 | 0.6197 | |
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| 0.648 | 0.21 | 1000 | 0.5950 | |
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| 0.6307 | 0.32 | 1500 | 0.5712 | |
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| 0.6847 | 0.43 | 2000 | 0.5361 | |
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| 0.5841 | 0.54 | 2500 | 0.5333 | |
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| 0.5418 | 0.64 | 3000 | 0.5195 | |
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| 0.5303 | 0.75 | 3500 | 0.5068 | |
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| 0.5555 | 0.86 | 4000 | 0.4948 | |
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| 0.5109 | 0.96 | 4500 | 0.4851 | |
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| 0.4823 | 1.07 | 5000 | 0.4866 | |
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| 0.491 | 1.18 | 5500 | 0.4793 | |
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| 0.441 | 1.28 | 6000 | 0.4825 | |
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| 0.4939 | 1.39 | 6500 | 0.4730 | |
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| 0.4425 | 1.5 | 7000 | 0.4715 | |
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| 0.4942 | 1.61 | 7500 | 0.4676 | |
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| 0.4256 | 1.71 | 8000 | 0.4593 | |
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| 0.5072 | 1.82 | 8500 | 0.4587 | |
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| 0.4215 | 1.93 | 9000 | 0.4561 | |
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| 0.3497 | 2.03 | 9500 | 0.4589 | |
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| 0.3899 | 2.14 | 10000 | 0.4575 | |
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| 0.3759 | 2.25 | 10500 | 0.4545 | |
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| 0.3637 | 2.35 | 11000 | 0.4535 | |
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| 0.3997 | 2.46 | 11500 | 0.4456 | |
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| 0.3496 | 2.57 | 12000 | 0.4466 | |
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| 0.3409 | 2.68 | 12500 | 0.4460 | |
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| 0.3575 | 2.78 | 13000 | 0.4440 | |
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| 0.3925 | 2.89 | 13500 | 0.4427 | |
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| 0.3228 | 3.0 | 14000 | 0.4432 | |
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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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