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--- |
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license: apache-2.0 |
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base_model: t5-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: T5_base_title_v3 |
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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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# T5_base_title_v3 |
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This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.8544 |
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- Rouge1: 0.4104 |
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- Rouge2: 0.212 |
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- Rougel: 0.3579 |
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- Rougelsum: 0.3576 |
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- Gen Len: 16.585 |
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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: 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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- num_epochs: 20 |
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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 | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |
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|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:| |
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| 2.2216 | 1.0 | 500 | 1.9241 | 0.3884 | 0.1992 | 0.3375 | 0.3371 | 16.168 | |
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| 1.9818 | 2.0 | 1000 | 1.8699 | 0.391 | 0.2002 | 0.342 | 0.341 | 16.386 | |
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| 1.8876 | 3.0 | 1500 | 1.8377 | 0.3972 | 0.2033 | 0.3447 | 0.3434 | 16.635 | |
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| 1.805 | 4.0 | 2000 | 1.8202 | 0.3981 | 0.2061 | 0.3482 | 0.3477 | 16.213 | |
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| 1.7422 | 5.0 | 2500 | 1.8180 | 0.395 | 0.2051 | 0.345 | 0.3445 | 16.74 | |
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| 1.6919 | 6.0 | 3000 | 1.8154 | 0.4042 | 0.2091 | 0.3526 | 0.3519 | 16.197 | |
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| 1.6426 | 7.0 | 3500 | 1.8160 | 0.4048 | 0.2094 | 0.3509 | 0.3506 | 16.546 | |
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| 1.5982 | 8.0 | 4000 | 1.8224 | 0.4088 | 0.2131 | 0.3556 | 0.3552 | 16.516 | |
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| 1.5615 | 9.0 | 4500 | 1.8219 | 0.4079 | 0.2121 | 0.3549 | 0.3545 | 16.474 | |
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| 1.5304 | 10.0 | 5000 | 1.8235 | 0.4059 | 0.2128 | 0.3548 | 0.3547 | 16.498 | |
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| 1.4996 | 11.0 | 5500 | 1.8299 | 0.4098 | 0.211 | 0.3569 | 0.3564 | 16.378 | |
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| 1.4735 | 12.0 | 6000 | 1.8349 | 0.4108 | 0.2129 | 0.3576 | 0.3572 | 16.672 | |
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| 1.4502 | 13.0 | 6500 | 1.8373 | 0.4103 | 0.2132 | 0.3566 | 0.3565 | 16.68 | |
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| 1.426 | 14.0 | 7000 | 1.8434 | 0.4092 | 0.2104 | 0.3559 | 0.3554 | 16.669 | |
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| 1.4137 | 15.0 | 7500 | 1.8442 | 0.4117 | 0.212 | 0.358 | 0.3576 | 16.547 | |
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| 1.401 | 16.0 | 8000 | 1.8503 | 0.4109 | 0.2126 | 0.3569 | 0.3567 | 16.552 | |
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| 1.3901 | 17.0 | 8500 | 1.8517 | 0.4115 | 0.2146 | 0.3601 | 0.36 | 16.553 | |
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| 1.3817 | 18.0 | 9000 | 1.8539 | 0.4104 | 0.2118 | 0.3572 | 0.3573 | 16.588 | |
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| 1.3696 | 19.0 | 9500 | 1.8553 | 0.4103 | 0.2126 | 0.3581 | 0.3578 | 16.568 | |
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| 1.369 | 20.0 | 10000 | 1.8544 | 0.4104 | 0.212 | 0.3579 | 0.3576 | 16.585 | |
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### Framework versions |
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- Transformers 4.37.2 |
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- Pytorch 2.1.2 |
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- Datasets 2.1.0 |
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- Tokenizers 0.15.1 |
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