End of training
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README.md
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---
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license: apache-2.0
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tags:
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- generated_from_trainer
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model-index:
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- name: t5-small-finetuned-turk-text-simplification
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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-small-finetuned-turk-text-simplification
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This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1001
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- Rouge2 Precision: 0.6825
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- Rouge2 Recall: 0.4542
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- Rouge2 Fmeasure: 0.5221
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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: 32
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- eval_batch_size: 32
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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: 5
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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 | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
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|:-------------:|:-----:|:----:|:---------------:|:----------------:|:-------------:|:---------------:|
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| 0.4318 | 1.0 | 500 | 0.1053 | 0.682 | 0.4533 | 0.5214 |
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| 0.0977 | 2.0 | 1000 | 0.1019 | 0.683 | 0.4545 | 0.5225 |
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| 0.0938 | 3.0 | 1500 | 0.1010 | 0.6828 | 0.4547 | 0.5226 |
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| 0.0916 | 4.0 | 2000 | 0.1003 | 0.6829 | 0.4545 | 0.5225 |
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| 0.0906 | 5.0 | 2500 | 0.1001 | 0.6825 | 0.4542 | 0.5221 |
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### Framework versions
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- Transformers 4.21.3
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- Pytorch 1.12.1+cu113
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- Datasets 2.4.0
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- Tokenizers 0.12.1
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pytorch_model.bin
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