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--- |
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license: apache-2.0 |
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base_model: google/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: 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: train |
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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: 2.98 |
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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-base-xlsum |
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This model is a fine-tuned version of [google/mt5-base](https://huggingface.co/google/mt5-base) on the xlsum dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.0396 |
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- Rouge1: 2.98 |
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- Rouge2: 0.1333 |
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- Rougel: 3.0267 |
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- Rougelsum: 2.9933 |
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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: 2 |
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- eval_batch_size: 2 |
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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: 4 |
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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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| 5.3745 | 1.0 | 500 | 2.5041 | 1.0696 | 0.13 | 1.062 | 1.0629 | |
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| 3.413 | 2.0 | 1000 | 2.2178 | 1.8333 | 0.1333 | 1.84 | 1.8633 | |
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| 3.1052 | 3.0 | 1500 | 2.0844 | 3.14 | 0.2667 | 3.18 | 3.1733 | |
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| 2.9673 | 4.0 | 2000 | 2.0396 | 2.98 | 0.1333 | 3.0267 | 2.9933 | |
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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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