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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-finetuned |
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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-finetuned |
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This model is a fine-tuned version of [UrukHan/t5-russian-spell](https://huggingface.co/UrukHan/t5-russian-spell) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0737 |
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- Rouge1: 25.3988 |
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- Rouge2: 11.756 |
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- Rougel: 25.051 |
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- Rougelsum: 25.2041 |
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- Gen Len: 41.3929 |
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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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| 0.1861 | 0.07 | 1000 | 0.1074 | 24.351 | 9.9107 | 24.0512 | 24.1443 | 41.4375 | |
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| 0.1629 | 0.14 | 2000 | 0.0918 | 25.1414 | 11.3393 | 24.8541 | 24.9175 | 41.3839 | |
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| 0.1545 | 0.21 | 3000 | 0.0898 | 25.2909 | 11.5882 | 24.981 | 25.0772 | 41.2857 | |
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| 0.1507 | 0.29 | 4000 | 0.0860 | 25.1414 | 11.3393 | 24.8541 | 24.9175 | 41.3571 | |
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| 0.1472 | 0.36 | 5000 | 0.0823 | 25.2909 | 11.5882 | 24.981 | 25.0772 | 41.3661 | |
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| 0.1417 | 0.43 | 6000 | 0.0794 | 24.6565 | 10.2976 | 24.265 | 24.4006 | 41.4107 | |
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| 0.1411 | 0.5 | 7000 | 0.0788 | 25.1414 | 11.3393 | 24.8541 | 24.9175 | 41.3482 | |
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| 0.1395 | 0.57 | 8000 | 0.0786 | 25.2909 | 11.5882 | 24.981 | 25.0772 | 41.3125 | |
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| 0.1318 | 0.64 | 9000 | 0.0774 | 25.2909 | 11.5882 | 24.981 | 25.0772 | 41.3929 | |
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| 0.1336 | 0.72 | 10000 | 0.0758 | 25.2394 | 11.5476 | 24.9777 | 25.0511 | 41.3839 | |
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| 0.1332 | 0.79 | 11000 | 0.0743 | 25.2394 | 11.5476 | 24.9777 | 25.0511 | 41.3482 | |
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| 0.1309 | 0.86 | 12000 | 0.0734 | 25.2394 | 11.5476 | 24.9777 | 25.0511 | 41.3393 | |
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| 0.1264 | 0.93 | 13000 | 0.0737 | 25.3988 | 11.756 | 25.051 | 25.2041 | 41.3929 | |
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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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