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--- |
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library_name: transformers |
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license: mit |
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base_model: cointegrated/rut5-base-absum |
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tags: |
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- summarization |
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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: rut5-base-absum-finetuned-summ |
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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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# rut5-base-absum-finetuned-summ |
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This model is a fine-tuned version of [cointegrated/rut5-base-absum](https://huggingface.co/cointegrated/rut5-base-absum) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6039 |
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- Rouge1: 97.0122 |
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- Rouge2: 94.5148 |
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- Rougel: 97.0189 |
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- Rougelsum: 96.9668 |
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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: 5.6e-05 |
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- train_batch_size: 64 |
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- eval_batch_size: 64 |
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- seed: 42 |
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- num_epochs: 8 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | |
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|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:| |
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| No log | 1.0 | 15 | 0.9642 | 88.9988 | 70.6048 | 88.8684 | 88.9803 | |
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| No log | 2.0 | 30 | 0.7765 | 94.6938 | 86.9198 | 94.7219 | 94.6778 | |
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| No log | 3.0 | 45 | 0.6995 | 96.1002 | 90.9986 | 96.058 | 96.058 | |
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| No log | 4.0 | 60 | 0.6596 | 96.0421 | 92.2644 | 96.067 | 96.0107 | |
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| No log | 5.0 | 75 | 0.6294 | 96.5868 | 93.2489 | 96.5836 | 96.5625 | |
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| No log | 6.0 | 90 | 0.6172 | 96.4605 | 92.827 | 96.4538 | 96.4071 | |
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| No log | 7.0 | 105 | 0.6091 | 97.0122 | 94.5148 | 97.0189 | 96.9668 | |
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| 1.0079 | 8.0 | 120 | 0.6039 | 97.0122 | 94.5148 | 97.0189 | 96.9668 | |
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### Framework versions |
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- Transformers 4.53.0 |
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- Pytorch 2.2.1+cu118 |
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- Datasets 4.0.0 |
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- Tokenizers 0.21.4 |
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