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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: google/flan-t5-base |
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tags: |
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- generated_from_trainer |
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datasets: |
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- mlsum |
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metrics: |
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- rouge |
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model-index: |
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- name: flan-t5-base-turkish-summarisation |
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results: |
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- task: |
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name: Sequence-to-sequence Language Modeling |
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type: text2text-generation |
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dataset: |
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name: mlsum |
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type: mlsum |
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config: tu |
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split: validation |
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args: tu |
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metrics: |
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- name: Rouge1 |
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type: rouge |
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value: 17.7215 |
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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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# flan-t5-base-turkish-summarisation |
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This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on the mlsum dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.2759 |
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- Rouge1: 17.7215 |
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- Rouge2: 11.6449 |
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- Rougel: 17.1215 |
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- Rougelsum: 17.0317 |
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- Gen Len: 20.0 |
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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: 5e-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: 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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- training_steps: 1000 |
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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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| 1.5856 | 0.0802 | 200 | 1.3164 | 18.0769 | 11.7482 | 17.3132 | 17.32 | 20.0 | |
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| 1.4888 | 0.1604 | 400 | 1.2901 | 17.6893 | 11.6682 | 16.9148 | 16.8964 | 20.0 | |
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| 1.4787 | 0.2407 | 600 | 1.2827 | 17.5252 | 11.5143 | 16.8586 | 16.8281 | 20.0 | |
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| 1.488 | 0.3209 | 800 | 1.2637 | 17.8913 | 11.7712 | 17.1369 | 17.0949 | 20.0 | |
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| 1.4105 | 0.4011 | 1000 | 1.2759 | 17.7215 | 11.6449 | 17.1215 | 17.0317 | 20.0 | |
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### Framework versions |
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- Transformers 4.48.0 |
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- Pytorch 2.2.2 |
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- Datasets 3.2.0 |
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- Tokenizers 0.21.0 |
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