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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-t5-909
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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-t5-909
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This model is a fine-tuned version of [sberbank-ai/ruT5-large](https://huggingface.co/sberbank-ai/ruT5-large) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0814
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- Rouge1: 18.2203
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- Rouge2: 5.9322
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- Rougel: 17.7966
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- Rougelsum: 18.2203
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- Gen Len: 42.0424
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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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| 0.3022 | 0.1 | 1500 | 0.1563 | 18.2203 | 5.9322 | 17.7966 | 18.2203 | 43.4492 |
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| 0.2274 | 0.2 | 3000 | 0.1311 | 18.2203 | 5.9322 | 17.7966 | 18.2203 | 42.3814 |
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| 0.2001 | 0.31 | 4500 | 0.1128 | 18.2203 | 5.9322 | 17.7966 | 18.2203 | 41.9407 |
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| 0.1757 | 0.41 | 6000 | 0.1063 | 18.2203 | 5.9322 | 17.7966 | 18.2203 | 42.2542 |
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| 0.1612 | 0.51 | 7500 | 0.1002 | 17.9379 | 5.0847 | 17.5141 | 17.7966 | 42.339 |
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| 0.1718 | 0.61 | 9000 | 0.0921 | 18.2203 | 5.9322 | 17.7966 | 18.2203 | 42.0508 |
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| 0.1678 | 0.72 | 10500 | 0.0834 | 17.7966 | 5.0847 | 17.3729 | 17.7966 | 41.9831 |
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| 0.1407 | 0.82 | 12000 | 0.0793 | 18.2203 | 5.9322 | 17.7966 | 18.2203 | 42.2119 |
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| 0.1447 | 0.92 | 13500 | 0.0814 | 18.2203 | 5.9322 | 17.7966 | 18.2203 | 42.0424 |
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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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