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--- |
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library_name: transformers |
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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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- bleu |
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model-index: |
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- name: results |
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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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# results |
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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: 2.6147 |
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- Bleu: 0.2098 |
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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: 0.0002 |
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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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- num_epochs: 30 |
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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 | Bleu | |
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|:-------------:|:-----:|:-----:|:---------------:|:------:| |
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| No log | 1.0 | 414 | 1.5123 | 0.1913 | |
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| 1.8064 | 2.0 | 828 | 1.5254 | 0.2027 | |
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| 1.1389 | 3.0 | 1242 | 1.5991 | 0.1996 | |
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| 0.771 | 4.0 | 1656 | 1.7113 | 0.2013 | |
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| 0.5395 | 5.0 | 2070 | 1.8532 | 0.2015 | |
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| 0.5395 | 6.0 | 2484 | 1.9543 | 0.1955 | |
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| 0.3855 | 7.0 | 2898 | 2.0825 | 0.2021 | |
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| 0.2794 | 8.0 | 3312 | 2.1461 | 0.1981 | |
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| 0.2203 | 9.0 | 3726 | 2.2048 | 0.2049 | |
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| 0.1833 | 10.0 | 4140 | 2.2585 | 0.1997 | |
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| 0.154 | 11.0 | 4554 | 2.2970 | 0.2018 | |
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| 0.154 | 12.0 | 4968 | 2.3328 | 0.2013 | |
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| 0.1266 | 13.0 | 5382 | 2.3380 | 0.2012 | |
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| 0.1054 | 14.0 | 5796 | 2.4021 | 0.2026 | |
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| 0.0905 | 15.0 | 6210 | 2.4106 | 0.2005 | |
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| 0.0776 | 16.0 | 6624 | 2.4528 | 0.1988 | |
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| 0.0665 | 17.0 | 7038 | 2.4778 | 0.2017 | |
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| 0.0665 | 18.0 | 7452 | 2.5210 | 0.2031 | |
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| 0.0563 | 19.0 | 7866 | 2.5157 | 0.2029 | |
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| 0.0487 | 20.0 | 8280 | 2.5245 | 0.1998 | |
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| 0.0411 | 21.0 | 8694 | 2.5513 | 0.2016 | |
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| 0.0346 | 22.0 | 9108 | 2.5436 | 0.1994 | |
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| 0.0304 | 23.0 | 9522 | 2.5845 | 0.1996 | |
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| 0.0304 | 24.0 | 9936 | 2.5827 | 0.2005 | |
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| 0.0237 | 25.0 | 10350 | 2.5879 | 0.2067 | |
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| 0.0201 | 26.0 | 10764 | 2.5744 | 0.2050 | |
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| 0.0177 | 27.0 | 11178 | 2.6031 | 0.2091 | |
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| 0.0151 | 28.0 | 11592 | 2.5932 | 0.2099 | |
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| 0.0133 | 29.0 | 12006 | 2.6221 | 0.2105 | |
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| 0.0133 | 30.0 | 12420 | 2.6147 | 0.2098 | |
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### Framework versions |
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- Transformers 4.52.2 |
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- Pytorch 2.6.0+cu124 |
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- Datasets 3.6.0 |
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- Tokenizers 0.21.1 |
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