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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-01 |
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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-01 |
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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: 0.2094 |
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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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| 0.3418 | 0.11 | 500 | 0.3102 | |
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| 0.3315 | 0.21 | 1000 | 0.2811 | |
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| 0.3479 | 0.32 | 1500 | 0.2585 | |
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| 0.308 | 0.43 | 2000 | 0.2609 | |
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| 0.2716 | 0.54 | 2500 | 0.2549 | |
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| 0.2845 | 0.64 | 3000 | 0.2442 | |
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| 0.2781 | 0.75 | 3500 | 0.2379 | |
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| 0.2893 | 0.86 | 4000 | 0.2314 | |
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| 0.2581 | 0.96 | 4500 | 0.2297 | |
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| 0.2269 | 1.07 | 5000 | 0.2334 | |
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| 0.2274 | 1.18 | 5500 | 0.2272 | |
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| 0.2053 | 1.28 | 6000 | 0.2305 | |
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| 0.2062 | 1.39 | 6500 | 0.2246 | |
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| 0.241 | 1.5 | 7000 | 0.2215 | |
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| 0.1625 | 1.61 | 7500 | 0.2239 | |
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| 0.2179 | 1.71 | 8000 | 0.2181 | |
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| 0.2372 | 1.82 | 8500 | 0.2187 | |
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| 0.2116 | 1.93 | 9000 | 0.2115 | |
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| 0.1625 | 2.03 | 9500 | 0.2168 | |
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| 0.187 | 2.14 | 10000 | 0.2170 | |
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| 0.159 | 2.25 | 10500 | 0.2163 | |
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| 0.1741 | 2.35 | 11000 | 0.2144 | |
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| 0.1964 | 2.46 | 11500 | 0.2111 | |
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| 0.1679 | 2.57 | 12000 | 0.2117 | |
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| 0.1662 | 2.68 | 12500 | 0.2096 | |
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| 0.1436 | 2.78 | 13000 | 0.2107 | |
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| 0.1875 | 2.89 | 13500 | 0.2099 | |
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| 0.1656 | 3.0 | 14000 | 0.2094 | |
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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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