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--- |
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license: apache-2.0 |
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base_model: google/mt5-small |
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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: mt5-small-finetuned-tr-news |
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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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# mt5-small-finetuned-tr-news |
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This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.3748 |
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- Rouge1: 25.2124 |
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- Rouge2: 13.3894 |
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- Rougel: 22.4063 |
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- Rougelsum: 22.9668 |
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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: 8 |
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- eval_batch_size: 8 |
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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: 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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| 5.5375 | 1.0 | 875 | 2.5866 | 22.5826 | 11.7162 | 19.8221 | 20.1884 | |
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| 3.3129 | 2.0 | 1750 | 2.5237 | 23.8445 | 12.7539 | 21.3485 | 21.7204 | |
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| 3.0876 | 3.0 | 2625 | 2.4728 | 24.1288 | 12.5373 | 21.4068 | 21.8723 | |
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| 2.9685 | 4.0 | 3500 | 2.4348 | 25.3884 | 13.3569 | 22.5336 | 23.0989 | |
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| 2.8886 | 5.0 | 4375 | 2.4043 | 25.5798 | 13.7628 | 22.7085 | 23.2025 | |
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| 2.836 | 6.0 | 5250 | 2.3813 | 24.93 | 13.2058 | 22.2455 | 22.6959 | |
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| 2.8069 | 7.0 | 6125 | 2.3800 | 24.8104 | 12.9556 | 22.1114 | 22.6108 | |
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| 2.7813 | 8.0 | 7000 | 2.3748 | 25.2124 | 13.3894 | 22.4063 | 22.9668 | |
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### Framework versions |
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- Transformers 4.34.0 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.14.5 |
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- Tokenizers 0.14.1 |
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