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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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metrics: |
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- rouge |
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model-index: |
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- name: mt5-large-gramatika161k-b16-lr0.001 |
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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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# mt5-large-gramatika161k-b16-lr0.001 |
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This model is a fine-tuned version of [google/mt5-large](https://huggingface.co/google/mt5-large) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1429 |
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- Rouge1: 71.0622 |
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- Rouge2: 65.0219 |
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- Rougel: 70.921 |
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- Rougelsum: 70.9407 |
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- Gen Len: 18.3295 |
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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: 0.001 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- optimizer: Adafactor |
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- lr_scheduler_type: linear |
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- num_epochs: 5 |
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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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| 0.3954 | 0.63 | 5000 | 0.1851 | 69.5715 | 62.3503 | 69.3784 | 69.3899 | 18.3461 | |
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| 0.1746 | 1.27 | 10000 | 0.1537 | 70.6244 | 64.1779 | 70.4518 | 70.4717 | 18.3410 | |
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| 0.123 | 1.9 | 15000 | 0.1429 | 71.0622 | 65.0219 | 70.921 | 70.9407 | 18.3295 | |
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| 0.0758 | 2.54 | 20000 | 0.1468 | 71.5151 | 65.7486 | 71.3742 | 71.3959 | 18.3246 | |
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| 0.0568 | 3.17 | 25000 | 0.1603 | 71.6869 | 66.1031 | 71.5594 | 71.5794 | 18.3302 | |
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| 0.0327 | 3.81 | 30000 | 0.1556 | 71.9011 | 66.4738 | 71.7817 | 71.8013 | 18.3311 | |
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| 0.0196 | 4.44 | 35000 | 0.1782 | 72.0041 | 66.6645 | 71.886 | 71.9038 | 18.3293 | |
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### Framework versions |
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- Transformers 4.30.1 |
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- Pytorch 1.11.0a0+b6df043 |
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- Datasets 2.12.0 |
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- Tokenizers 0.13.3 |
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