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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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metrics: |
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- rouge |
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model-index: |
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- name: mt5-small-finetuned-news-summary-model-2 |
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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-small-finetuned-news-summary-model-2 |
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This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.5813 |
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- Rouge1: 29.4322 |
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- Rouge2: 11.4361 |
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- Rougel: 26.3875 |
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- Rougelsum: 26.297 |
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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: 4e-05 |
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- train_batch_size: 10 |
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- eval_batch_size: 10 |
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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: 12 |
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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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| 9.2632 | 0.9972 | 351 | 3.7059 | 17.3365 | 5.2307 | 15.438 | 15.3776 | |
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| 4.6719 | 1.9943 | 702 | 3.0896 | 19.5787 | 6.8278 | 18.0637 | 18.0255 | |
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| 4.1356 | 2.9915 | 1053 | 2.8713 | 22.5668 | 8.2899 | 20.551 | 20.5232 | |
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| 3.7852 | 3.9886 | 1404 | 2.7729 | 25.7974 | 9.9158 | 23.2398 | 23.2198 | |
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| 3.6194 | 4.9858 | 1755 | 2.7038 | 26.2572 | 10.0034 | 24.0326 | 23.9956 | |
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| 3.4864 | 5.9830 | 2106 | 2.6714 | 26.8149 | 9.9056 | 24.2704 | 24.1399 | |
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| 3.3965 | 6.9801 | 2457 | 2.6361 | 27.5399 | 10.3609 | 24.8286 | 24.7628 | |
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| 3.3422 | 7.9773 | 2808 | 2.6194 | 28.0298 | 10.6938 | 25.1678 | 25.0924 | |
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| 3.2879 | 8.9744 | 3159 | 2.5976 | 28.2324 | 10.6412 | 25.2803 | 25.1804 | |
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| 3.2391 | 9.9716 | 3510 | 2.5894 | 29.0155 | 11.174 | 25.9995 | 25.8843 | |
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| 3.2128 | 10.9688 | 3861 | 2.5854 | 29.3283 | 11.477 | 26.2235 | 26.1278 | |
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| 3.2214 | 11.9659 | 4212 | 2.5813 | 29.4322 | 11.4361 | 26.3875 | 26.297 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.19.2 |
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- Tokenizers 0.19.1 |
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