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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_v4 |
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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_v4 |
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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: 1.6697 |
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- Rouge1: 0.4305 |
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- Rouge2: 0.2304 |
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- Rougel: 0.3728 |
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- Rougelsum: 0.3729 |
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- Gen Len: 16.6586 |
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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: 15 |
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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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| 1.9653 | 1.0 | 2019 | 1.7927 | 0.4092 | 0.2145 | 0.3528 | 0.3528 | 16.6021 | |
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| 1.828 | 2.0 | 4038 | 1.7374 | 0.4148 | 0.217 | 0.3557 | 0.3558 | 16.7601 | |
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| 1.7597 | 3.0 | 6057 | 1.7053 | 0.4183 | 0.2199 | 0.3595 | 0.3594 | 16.8878 | |
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| 1.6787 | 4.0 | 8076 | 1.6875 | 0.4221 | 0.224 | 0.3649 | 0.3647 | 16.6098 | |
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| 1.6361 | 5.0 | 10095 | 1.6730 | 0.4227 | 0.2229 | 0.3655 | 0.3657 | 16.6044 | |
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| 1.6032 | 6.0 | 12114 | 1.6679 | 0.4266 | 0.227 | 0.3696 | 0.3697 | 16.4617 | |
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| 1.5701 | 7.0 | 14133 | 1.6657 | 0.4265 | 0.2273 | 0.3694 | 0.3692 | 16.4184 | |
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| 1.5359 | 8.0 | 16152 | 1.6677 | 0.4273 | 0.2274 | 0.3695 | 0.3695 | 16.5704 | |
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| 1.5136 | 9.0 | 18171 | 1.6639 | 0.4271 | 0.2278 | 0.3697 | 0.3697 | 16.5989 | |
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| 1.4776 | 10.0 | 20190 | 1.6641 | 0.4291 | 0.2297 | 0.3723 | 0.3722 | 16.5137 | |
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| 1.4507 | 11.0 | 22209 | 1.6650 | 0.4307 | 0.2303 | 0.372 | 0.3718 | 16.5868 | |
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| 1.437 | 12.0 | 24228 | 1.6654 | 0.4277 | 0.2274 | 0.3711 | 0.3711 | 16.7277 | |
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| 1.4428 | 13.0 | 26247 | 1.6689 | 0.4296 | 0.2287 | 0.3714 | 0.3715 | 16.7078 | |
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| 1.4183 | 14.0 | 28266 | 1.6697 | 0.4307 | 0.2301 | 0.3726 | 0.3725 | 16.6979 | |
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| 1.4244 | 15.0 | 30285 | 1.6697 | 0.4305 | 0.2304 | 0.3728 | 0.3729 | 16.6586 | |
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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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