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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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metrics: |
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- rouge |
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model-index: |
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- name: xsum_1677_bart-base |
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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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# xsum_1677_bart-base |
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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: 0.6469 |
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- Rouge1: 0.3879 |
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- Rouge2: 0.1787 |
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- Rougel: 0.3238 |
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- Rougelsum: 0.3238 |
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- Gen Len: 19.6644 |
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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: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 16 |
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- total_train_batch_size: 128 |
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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: 500 |
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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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| 0.8336 | 0.31 | 500 | 0.7274 | 0.3493 | 0.139 | 0.2847 | 0.2847 | 19.511 | |
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| 0.7963 | 0.63 | 1000 | 0.6994 | 0.3637 | 0.1506 | 0.2977 | 0.2976 | 19.6179 | |
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| 0.7543 | 0.94 | 1500 | 0.6876 | 0.365 | 0.1531 | 0.2999 | 0.2999 | 19.5356 | |
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| 0.7461 | 1.25 | 2000 | 0.6795 | 0.3709 | 0.1584 | 0.3052 | 0.3051 | 19.6224 | |
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| 0.7193 | 1.57 | 2500 | 0.6739 | 0.3684 | 0.1593 | 0.3048 | 0.3047 | 19.5721 | |
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| 0.7225 | 1.88 | 3000 | 0.6666 | 0.371 | 0.16 | 0.3063 | 0.3063 | 19.5672 | |
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| 0.6779 | 2.2 | 3500 | 0.6660 | 0.3745 | 0.1632 | 0.31 | 0.31 | 19.5619 | |
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| 0.673 | 2.51 | 4000 | 0.6618 | 0.3763 | 0.1653 | 0.3117 | 0.3117 | 19.6738 | |
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| 0.6848 | 2.82 | 4500 | 0.6578 | 0.3803 | 0.168 | 0.3145 | 0.3145 | 19.6308 | |
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| 0.6526 | 3.14 | 5000 | 0.6581 | 0.3803 | 0.1679 | 0.3141 | 0.3141 | 19.6503 | |
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| 0.6497 | 3.45 | 5500 | 0.6555 | 0.3776 | 0.1681 | 0.3132 | 0.3133 | 19.643 | |
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| 0.6483 | 3.76 | 6000 | 0.6520 | 0.3803 | 0.17 | 0.3153 | 0.3152 | 19.6666 | |
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| 0.6249 | 4.08 | 6500 | 0.6535 | 0.383 | 0.1736 | 0.3186 | 0.3185 | 19.6371 | |
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| 0.628 | 4.39 | 7000 | 0.6531 | 0.3825 | 0.1728 | 0.3181 | 0.318 | 19.6159 | |
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| 0.6288 | 4.7 | 7500 | 0.6495 | 0.3827 | 0.1727 | 0.3181 | 0.3181 | 19.6695 | |
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| 0.5921 | 5.02 | 8000 | 0.6509 | 0.3825 | 0.173 | 0.318 | 0.318 | 19.6447 | |
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| 0.6003 | 5.33 | 8500 | 0.6513 | 0.3833 | 0.1742 | 0.3198 | 0.3197 | 19.6866 | |
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| 0.5922 | 5.65 | 9000 | 0.6482 | 0.3837 | 0.1737 | 0.3195 | 0.3195 | 19.719 | |
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| 0.5878 | 5.96 | 9500 | 0.6483 | 0.3824 | 0.1737 | 0.3185 | 0.3185 | 19.6156 | |
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| 0.5646 | 6.27 | 10000 | 0.6503 | 0.3851 | 0.1754 | 0.3203 | 0.3204 | 19.6693 | |
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| 0.5753 | 6.59 | 10500 | 0.6473 | 0.3855 | 0.1761 | 0.3206 | 0.3206 | 19.6873 | |
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| 0.579 | 6.9 | 11000 | 0.6467 | 0.3861 | 0.1769 | 0.3223 | 0.3223 | 19.6635 | |
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| 0.5865 | 7.21 | 11500 | 0.6480 | 0.3862 | 0.176 | 0.3213 | 0.3212 | 19.7016 | |
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| 0.5746 | 7.53 | 12000 | 0.6480 | 0.3878 | 0.1785 | 0.3235 | 0.3236 | 19.6531 | |
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| 0.5678 | 7.84 | 12500 | 0.6460 | 0.3868 | 0.1776 | 0.3221 | 0.322 | 19.7039 | |
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| 0.5584 | 8.15 | 13000 | 0.6485 | 0.3875 | 0.178 | 0.3233 | 0.3233 | 19.6565 | |
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| 0.5484 | 8.47 | 13500 | 0.6477 | 0.3867 | 0.1777 | 0.3223 | 0.3224 | 19.6937 | |
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| 0.558 | 8.78 | 14000 | 0.6468 | 0.3873 | 0.1781 | 0.323 | 0.323 | 19.6823 | |
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| 0.5482 | 9.1 | 14500 | 0.6475 | 0.3878 | 0.1787 | 0.3231 | 0.3232 | 19.6896 | |
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| 0.5551 | 9.41 | 15000 | 0.6475 | 0.388 | 0.1783 | 0.3238 | 0.3237 | 19.666 | |
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| 0.5488 | 9.72 | 15500 | 0.6469 | 0.3879 | 0.1787 | 0.3238 | 0.3238 | 19.6644 | |
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### Framework versions |
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- Transformers 4.37.2 |
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- Pytorch 2.2.0+cu121 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.1 |
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