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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_title_generation |
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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_title_generation |
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This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.8317 |
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- Rouge1: 38.8271 |
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- Rouge2: 15.9699 |
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- Rougel: 37.4629 |
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- Rougelsum: 37.4611 |
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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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| 2.9375 | 1.0 | 1715 | 2.1953 | 32.8581 | 12.0123 | 31.7428 | 31.7415 | |
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| 2.7861 | 2.0 | 3430 | 2.0516 | 34.7374 | 12.8384 | 33.5105 | 33.5139 | |
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| 2.5732 | 3.0 | 5145 | 1.9641 | 36.3304 | 14.2331 | 35.0356 | 35.0547 | |
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| 2.434 | 4.0 | 6860 | 1.9057 | 36.696 | 14.5408 | 35.4881 | 35.48 | |
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| 2.3377 | 5.0 | 8575 | 1.8784 | 37.5708 | 14.9623 | 36.232 | 36.2245 | |
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| 2.2665 | 6.0 | 10290 | 1.8506 | 38.0536 | 15.35 | 36.7089 | 36.6998 | |
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| 2.2281 | 7.0 | 12005 | 1.8379 | 38.6899 | 16.0013 | 37.3522 | 37.3469 | |
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| 2.2025 | 8.0 | 13720 | 1.8317 | 38.8271 | 15.9699 | 37.4629 | 37.4611 | |
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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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