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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-4000 |
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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: 4.2038 |
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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-4000 |
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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: 1.7909 |
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- Rouge1: 4.2038 |
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- Rouge2: 0.6736 |
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- Rougel: 4.1229 |
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- Rougelsum: 4.1353 |
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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: 6 |
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- eval_batch_size: 6 |
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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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| 2.871 | 1.0 | 7201 | 1.9992 | 3.157 | 0.5155 | 3.1283 | 3.1298 | |
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| 2.3902 | 2.0 | 14402 | 1.9162 | 3.6231 | 0.595 | 3.5878 | 3.6125 | |
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| 2.2273 | 3.0 | 21603 | 1.8681 | 3.8688 | 0.5949 | 3.8101 | 3.8106 | |
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| 2.1219 | 4.0 | 28804 | 1.8264 | 3.7935 | 0.58 | 3.741 | 3.7647 | |
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| 2.0448 | 5.0 | 36005 | 1.8062 | 3.9388 | 0.7156 | 3.8877 | 3.9098 | |
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| 1.9898 | 6.0 | 43206 | 1.8077 | 4.3916 | 0.8113 | 4.3133 | 4.327 | |
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| 1.9483 | 7.0 | 50407 | 1.7935 | 4.2474 | 0.7119 | 4.1732 | 4.197 | |
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| 1.9209 | 8.0 | 57608 | 1.7909 | 4.2038 | 0.6736 | 4.1229 | 4.1353 | |
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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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