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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: bart-with-pubmed-noise-data-0.1-v2 |
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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-with-pubmed-noise-data-0.1-v2 |
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This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co./facebook/bart-base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2115 |
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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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| 0.4161 | 0.11 | 500 | 0.3441 | |
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| 0.342 | 0.21 | 1000 | 0.3091 | |
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| 0.2694 | 0.32 | 1500 | 0.2969 | |
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| 0.3792 | 0.43 | 2000 | 0.2712 | |
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| 0.3219 | 0.54 | 2500 | 0.2601 | |
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| 0.3001 | 0.64 | 3000 | 0.2574 | |
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| 0.2606 | 0.75 | 3500 | 0.2489 | |
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| 0.2716 | 0.86 | 4000 | 0.2415 | |
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| 0.2714 | 0.96 | 4500 | 0.2382 | |
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| 0.2072 | 1.07 | 5000 | 0.2429 | |
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| 0.2111 | 1.18 | 5500 | 0.2377 | |
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| 0.1977 | 1.28 | 6000 | 0.2455 | |
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| 0.2171 | 1.39 | 6500 | 0.2309 | |
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| 0.1853 | 1.5 | 7000 | 0.2314 | |
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| 0.2436 | 1.61 | 7500 | 0.2269 | |
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| 0.171 | 1.71 | 8000 | 0.2220 | |
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| 0.2032 | 1.82 | 8500 | 0.2226 | |
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| 0.2028 | 1.93 | 9000 | 0.2175 | |
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| 0.1448 | 2.03 | 9500 | 0.2227 | |
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| 0.1447 | 2.14 | 10000 | 0.2216 | |
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| 0.1516 | 2.25 | 10500 | 0.2200 | |
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| 0.1294 | 2.35 | 11000 | 0.2197 | |
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| 0.1569 | 2.46 | 11500 | 0.2157 | |
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| 0.1505 | 2.57 | 12000 | 0.2160 | |
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| 0.152 | 2.68 | 12500 | 0.2151 | |
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| 0.1588 | 2.78 | 13000 | 0.2117 | |
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| 0.1451 | 2.89 | 13500 | 0.2134 | |
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| 0.1644 | 3.0 | 14000 | 0.2115 | |
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### Framework versions |
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- Transformers 4.37.2 |
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- Pytorch 2.1.2+cu121 |
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- Datasets 2.17.0 |
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- Tokenizers 0.15.1 |
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