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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-finetuned-scitldr |
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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-finetuned-scitldr |
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This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 3.1055 |
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- Rouge1: 23.6222 |
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- Rouge2: 10.2432 |
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- Rougel: 19.702 |
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- Rougelsum: 20.9458 |
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- Gen Len: 18.979 |
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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: 4e-05 |
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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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- 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: 1 |
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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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| 2.4272 | 0.1 | 100 | 3.1951 | 23.0447 | 9.7818 | 19.0676 | 20.1677 | 18.9532 | |
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| 2.0362 | 0.2 | 200 | 3.1715 | 23.5443 | 10.1156 | 19.5788 | 20.6995 | 18.9483 | |
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| 2.188 | 0.3 | 300 | 3.1067 | 24.2387 | 10.3059 | 20.0964 | 21.2592 | 18.9338 | |
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| 2.0312 | 0.4 | 400 | 3.1092 | 23.3168 | 10.1308 | 19.4275 | 20.611 | 18.9742 | |
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| 2.012 | 0.5 | 500 | 3.1189 | 23.6989 | 10.3005 | 19.7634 | 20.9462 | 18.9758 | |
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| 2.0581 | 0.6 | 600 | 3.1191 | 23.6818 | 10.2636 | 19.7953 | 20.9935 | 18.9774 | |
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| 2.0067 | 0.7 | 700 | 3.1297 | 23.8476 | 10.5139 | 19.9696 | 21.1594 | 18.9774 | |
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| 2.0049 | 0.8 | 800 | 3.1150 | 23.6929 | 10.3243 | 19.7895 | 21.0455 | 18.979 | |
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| 2.1839 | 0.9 | 900 | 3.1055 | 23.6222 | 10.2432 | 19.702 | 20.9458 | 18.979 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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