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--- |
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base_model: razent/SciFive-base-Pubmed_PMC |
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tags: |
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- generated_from_trainer |
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metrics: |
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- rouge |
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model-index: |
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- name: scifive_ten_epoch |
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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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# scifive_ten_epoch |
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This model is a fine-tuned version of [razent/SciFive-base-Pubmed_PMC](https://huggingface.co/razent/SciFive-base-Pubmed_PMC) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.7913 |
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- Rouge1: 0.366 |
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- Rouge2: 0.2107 |
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- Rougel: 0.3132 |
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- Rougelsum: 0.3131 |
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- Gen Len: 17.33 |
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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: 2e-05 |
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- train_batch_size: 4 |
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- eval_batch_size: 2 |
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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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- num_epochs: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:| |
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| No log | 1.0 | 275 | 2.2002 | 0.2752 | 0.1436 | 0.2395 | 0.24 | 17.32 | |
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| 2.3887 | 2.0 | 550 | 1.9610 | 0.347 | 0.2007 | 0.2959 | 0.2961 | 17.73 | |
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| 2.3887 | 3.0 | 825 | 1.8986 | 0.3664 | 0.2121 | 0.3098 | 0.3101 | 17.5 | |
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| 1.7972 | 4.0 | 1100 | 1.8486 | 0.3805 | 0.2309 | 0.3267 | 0.327 | 17.1 | |
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| 1.7972 | 5.0 | 1375 | 1.8232 | 0.372 | 0.2178 | 0.313 | 0.313 | 17.64 | |
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| 1.6528 | 6.0 | 1650 | 1.8005 | 0.3836 | 0.2271 | 0.3208 | 0.3209 | 17.44 | |
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| 1.6528 | 7.0 | 1925 | 1.7969 | 0.3821 | 0.2278 | 0.3251 | 0.3253 | 17.25 | |
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| 1.5676 | 8.0 | 2200 | 1.7872 | 0.3806 | 0.2242 | 0.3224 | 0.323 | 17.3 | |
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| 1.5676 | 9.0 | 2475 | 1.7888 | 0.3697 | 0.2135 | 0.3135 | 0.3133 | 17.36 | |
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| 1.5288 | 10.0 | 2750 | 1.7913 | 0.366 | 0.2107 | 0.3132 | 0.3131 | 17.33 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.1 |
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