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update model card README.md
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README.md
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---
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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: speller-example__
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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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# speller-example__
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This model is a fine-tuned version of [sberbank-ai/ruT5-base](https://huggingface.co/sberbank-ai/ruT5-base) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1437
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- Rouge1: 19.7034
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- Rouge2: 8.7571
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- Rougel: 19.4209
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- Rougelsum: 19.774
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- Gen Len: 41.2542
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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: 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: 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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| 0.3549 | 0.1 | 1500 | 0.1935 | 19.7034 | 8.7571 | 19.4209 | 19.774 | 41.1356 |
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| 0.3863 | 0.2 | 3000 | 0.1830 | 19.7034 | 8.7571 | 19.4209 | 19.774 | 41.1864 |
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| 0.3164 | 0.31 | 4500 | 0.1746 | 19.5621 | 8.4746 | 19.2797 | 19.5621 | 41.2966 |
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| 0.367 | 0.41 | 6000 | 0.1690 | 19.7034 | 8.7571 | 19.4209 | 19.774 | 41.161 |
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| 0.3002 | 0.51 | 7500 | 0.1578 | 19.7034 | 8.7571 | 19.4209 | 19.774 | 41.2458 |
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| 0.3352 | 0.61 | 9000 | 0.1541 | 19.7034 | 8.7571 | 19.4209 | 19.774 | 41.3475 |
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| 0.2462 | 0.72 | 10500 | 0.1519 | 19.7034 | 8.7571 | 19.4209 | 19.774 | 41.3475 |
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| 0.2736 | 0.82 | 12000 | 0.1510 | 19.7034 | 8.7571 | 19.4209 | 19.774 | 41.2797 |
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| 0.2618 | 0.92 | 13500 | 0.1437 | 19.7034 | 8.7571 | 19.4209 | 19.774 | 41.2542 |
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### Framework versions
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- Transformers 4.26.0
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- Pytorch 1.13.1+cu116
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- Datasets 2.9.0
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- Tokenizers 0.13.2
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