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--- |
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license: apache-2.0 |
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base_model: google/long-t5-tglobal-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: long_t5 |
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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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# long_t5 |
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This model is a fine-tuned version of [google/long-t5-tglobal-base](https://huggingface.co/google/long-t5-tglobal-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.5158 |
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- Rouge1: 0.5214 |
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- Rouge2: 0.3347 |
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- Rougel: 0.4751 |
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- Rougelsum: 0.4746 |
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- Gen Len: 25.9513 |
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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: 4 |
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- eval_batch_size: 4 |
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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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### 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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| 2.232 | 1.0 | 1600 | 1.6810 | 0.4704 | 0.2861 | 0.4256 | 0.4251 | 26.6112 | |
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| 2.0229 | 2.0 | 3200 | 1.6167 | 0.4859 | 0.2991 | 0.4412 | 0.4407 | 26.1006 | |
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| 1.9239 | 3.0 | 4800 | 1.5805 | 0.4924 | 0.3049 | 0.4475 | 0.4468 | 26.8169 | |
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| 1.8454 | 4.0 | 6400 | 1.5669 | 0.4968 | 0.3093 | 0.4517 | 0.4511 | 25.925 | |
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| 1.7626 | 5.0 | 8000 | 1.5432 | 0.4973 | 0.3132 | 0.453 | 0.4525 | 26.4362 | |
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| 1.6995 | 6.0 | 9600 | 1.5352 | 0.5045 | 0.3188 | 0.4596 | 0.459 | 26.1219 | |
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| 1.682 | 7.0 | 11200 | 1.5255 | 0.5066 | 0.3198 | 0.4613 | 0.4609 | 26.1581 | |
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| 1.6286 | 8.0 | 12800 | 1.5210 | 0.5113 | 0.3245 | 0.4663 | 0.466 | 26.1725 | |
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| 1.593 | 9.0 | 14400 | 1.5195 | 0.5102 | 0.3235 | 0.464 | 0.4638 | 25.8944 | |
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| 1.5784 | 10.0 | 16000 | 1.5166 | 0.5133 | 0.3265 | 0.4665 | 0.4661 | 25.685 | |
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| 1.5615 | 11.0 | 17600 | 1.5135 | 0.5161 | 0.3284 | 0.47 | 0.4695 | 25.8681 | |
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| 1.5391 | 12.0 | 19200 | 1.5106 | 0.5156 | 0.3303 | 0.4703 | 0.4701 | 26.1781 | |
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| 1.5077 | 13.0 | 20800 | 1.5095 | 0.5177 | 0.3317 | 0.4724 | 0.4721 | 26.0456 | |
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| 1.4923 | 14.0 | 22400 | 1.5163 | 0.5185 | 0.3321 | 0.4728 | 0.4723 | 26.17 | |
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| 1.4545 | 15.0 | 24000 | 1.5128 | 0.5181 | 0.3337 | 0.4727 | 0.4724 | 25.8219 | |
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| 1.4489 | 16.0 | 25600 | 1.5135 | 0.5209 | 0.3349 | 0.4744 | 0.4743 | 26.0369 | |
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| 1.4481 | 17.0 | 27200 | 1.5153 | 0.5218 | 0.3349 | 0.4751 | 0.4748 | 26.1744 | |
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| 1.4287 | 18.0 | 28800 | 1.5134 | 0.521 | 0.335 | 0.4752 | 0.4747 | 25.9525 | |
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| 1.389 | 19.0 | 30400 | 1.5155 | 0.5212 | 0.3348 | 0.4756 | 0.4751 | 26.0369 | |
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| 1.4215 | 20.0 | 32000 | 1.5158 | 0.5214 | 0.3347 | 0.4751 | 0.4746 | 25.9513 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- Pytorch 2.3.1+cu118 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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