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--- |
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base_model: kravchenko/uk-mt5-base |
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tags: |
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- summarization |
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- generated_from_trainer |
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datasets: |
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- xlsum |
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metrics: |
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- rouge |
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model-index: |
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- name: uk-mt5-base-xlsum |
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results: |
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- task: |
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name: Sequence-to-sequence Language Modeling |
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type: text2text-generation |
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dataset: |
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name: xlsum |
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type: xlsum |
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config: ukrainian |
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split: validation |
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args: ukrainian |
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metrics: |
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- name: Rouge1 |
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type: rouge |
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value: 3.8556 |
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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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# uk-mt5-base-xlsum |
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This model is a fine-tuned version of [kravchenko/uk-mt5-base](https://huggingface.co/kravchenko/uk-mt5-base) on the xlsum dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.3660 |
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- Rouge1: 3.8556 |
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- Rouge2: 1.5556 |
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- Rougel: 3.7833 |
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- Rougelsum: 3.6889 |
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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: 5.6e-05 |
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- train_batch_size: 4 |
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- eval_batch_size: 4 |
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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: 8 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:| |
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| 5.31 | 1.0 | 375 | 2.5055 | 2.3333 | 0.8 | 2.3143 | 2.3238 | |
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| 3.254 | 2.0 | 750 | 2.4034 | 3.5444 | 1.1111 | 3.5333 | 3.4833 | |
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| 2.9813 | 3.0 | 1125 | 2.3844 | 3.7278 | 1.4444 | 3.6889 | 3.6333 | |
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| 2.8117 | 4.0 | 1500 | 2.3785 | 3.3222 | 1.1111 | 3.2556 | 3.2167 | |
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| 2.681 | 5.0 | 1875 | 2.3671 | 4.1667 | 1.5556 | 4.0667 | 4.0444 | |
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| 2.5825 | 6.0 | 2250 | 2.3705 | 3.6889 | 1.5556 | 3.6 | 3.5333 | |
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| 2.5151 | 7.0 | 2625 | 2.3654 | 3.6889 | 1.5556 | 3.6 | 3.5333 | |
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| 2.4798 | 8.0 | 3000 | 2.3660 | 3.8556 | 1.5556 | 3.7833 | 3.6889 | |
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### Framework versions |
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- Transformers 4.34.0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.5 |
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- Tokenizers 0.14.1 |
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