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--- |
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license: apache-2.0 |
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base_model: google-t5/t5-base |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: t5-abs-2309-1054-lr-0.001-bs-2-maxep-20 |
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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-abs-2309-1054-lr-0.001-bs-2-maxep-20 |
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This model is a fine-tuned version of [google-t5/t5-base](https://huggingface.co/google-t5/t5-base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: nan |
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- Rouge/rouge1: 0.0 |
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- Rouge/rouge2: 0.0 |
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- Rouge/rougel: 0.0 |
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- Rouge/rougelsum: 0.0 |
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- Bertscore/bertscore-precision: 0.0 |
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- Bertscore/bertscore-recall: 0.0 |
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- Bertscore/bertscore-f1: 0.0 |
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- Meteor: 0.0 |
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- Gen Len: 0.0 |
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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: 0.001 |
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- train_batch_size: 2 |
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- eval_batch_size: 2 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 4 |
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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_ratio: 0.1 |
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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 | Rouge/rouge1 | Rouge/rouge2 | Rouge/rougel | Rouge/rougelsum | Bertscore/bertscore-precision | Bertscore/bertscore-recall | Bertscore/bertscore-f1 | Meteor | Gen Len | |
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|:-------------:|:-----:|:----:|:---------------:|:------------:|:------------:|:------------:|:---------------:|:-----------------------------:|:--------------------------:|:----------------------:|:------:|:-------:| |
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| 1.0524 | 1.0 | 217 | 1.9798 | 0.4548 | 0.2064 | 0.3831 | 0.3848 | 0.8919 | 0.8942 | 0.8929 | 0.4177 | 41.2636 | |
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| 1.4167 | 2.0 | 434 | 1.9903 | 0.4327 | 0.1886 | 0.3657 | 0.3672 | 0.8947 | 0.8843 | 0.8893 | 0.3692 | 33.8545 | |
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| 1.3767 | 3.0 | 651 | 2.0041 | 0.4527 | 0.2062 | 0.3851 | 0.3862 | 0.8945 | 0.8927 | 0.8934 | 0.4073 | 38.0727 | |
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| 1.0766 | 4.0 | 868 | 2.0268 | 0.4611 | 0.2088 | 0.3905 | 0.3915 | 0.8985 | 0.8923 | 0.8952 | 0.4052 | 36.4182 | |
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| 1.0071 | 5.0 | 1085 | 2.3584 | 0.4183 | 0.1611 | 0.3443 | 0.3455 | 0.8901 | 0.8858 | 0.8877 | 0.3591 | 36.9909 | |
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| 1.1108 | 6.0 | 1302 | 2.5739 | 0.4169 | 0.1599 | 0.3463 | 0.3463 | 0.8895 | 0.8835 | 0.8861 | 0.3516 | 35.2636 | |
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| 1.2043 | 7.0 | 1519 | 2.7884 | 0.3995 | 0.1628 | 0.3339 | 0.3347 | 0.8717 | 0.8827 | 0.876 | 0.341 | 38.7364 | |
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| 1.24 | 8.0 | 1736 | 2.7884 | 0.3995 | 0.1628 | 0.3339 | 0.3347 | 0.8717 | 0.8827 | 0.876 | 0.341 | 38.7364 | |
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| 1.2303 | 9.0 | 1953 | 2.7884 | 0.3995 | 0.1628 | 0.3339 | 0.3347 | 0.8717 | 0.8827 | 0.876 | 0.341 | 38.7364 | |
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| 1.218 | 10.0 | 2170 | 2.7884 | 0.3995 | 0.1628 | 0.3339 | 0.3347 | 0.8717 | 0.8827 | 0.876 | 0.341 | 38.7364 | |
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| 1.2135 | 11.0 | 2387 | 2.7884 | 0.3995 | 0.1628 | 0.3339 | 0.3347 | 0.8717 | 0.8827 | 0.876 | 0.341 | 38.7364 | |
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| 1.2276 | 12.0 | 2604 | 2.7884 | 0.3995 | 0.1628 | 0.3339 | 0.3347 | 0.8717 | 0.8827 | 0.876 | 0.341 | 38.7364 | |
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| 1.2104 | 13.0 | 2821 | 2.7884 | 0.3995 | 0.1628 | 0.3339 | 0.3347 | 0.8717 | 0.8827 | 0.876 | 0.341 | 38.7364 | |
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| 1.2409 | 14.0 | 3038 | 2.7884 | 0.3995 | 0.1628 | 0.3339 | 0.3347 | 0.8717 | 0.8827 | 0.876 | 0.341 | 38.7364 | |
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| 4.1714 | 15.0 | 3255 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 0.0 | 16.0 | 3472 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 0.0 | 17.0 | 3689 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 0.0 | 18.0 | 3906 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 0.0 | 19.0 | 4123 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 0.0 | 20.0 | 4340 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
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### Framework versions |
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- Transformers 4.44.0 |
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- Pytorch 2.4.0 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
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