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--- |
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license: apache-2.0 |
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base_model: google/mt5-small |
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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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- gazeta |
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metrics: |
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- rouge |
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model-index: |
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- name: mt5-small-finetuned-gazeta-ru |
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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: gazeta |
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type: gazeta |
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config: default |
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split: validation |
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args: default |
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metrics: |
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- name: Rouge1 |
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type: rouge |
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value: 2.9422 |
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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-small-finetuned-gazeta-ru |
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This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the gazeta dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 3.3287 |
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- Rouge1: 2.9422 |
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- Rouge2: 0.25 |
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- Rougel: 2.9053 |
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- Rougelsum: 2.9131 |
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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: 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: 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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| 5.5708 | 1.0 | 1690 | 3.3106 | 1.8563 | 0.1911 | 1.8332 | 1.8348 | |
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| 4.0219 | 2.0 | 3380 | 3.3048 | 2.2018 | 0.1649 | 2.1978 | 2.2022 | |
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| 3.7276 | 3.0 | 5070 | 3.3320 | 3.2293 | 0.2173 | 3.194 | 3.2039 | |
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| 3.5835 | 4.0 | 6760 | 3.3308 | 3.2189 | 0.2932 | 3.1825 | 3.1841 | |
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| 3.4944 | 5.0 | 8450 | 3.3104 | 2.8833 | 0.1964 | 2.8521 | 2.8537 | |
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| 3.4203 | 6.0 | 10140 | 3.3032 | 2.9914 | 0.2723 | 2.9516 | 2.9542 | |
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| 3.3774 | 7.0 | 11830 | 3.3232 | 2.9982 | 0.3063 | 2.965 | 2.9642 | |
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| 3.348 | 8.0 | 13520 | 3.3287 | 2.9422 | 0.25 | 2.9053 | 2.9131 | |
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### Framework versions |
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- Transformers 4.42.4 |
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- Pytorch 2.3.1+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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