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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-multinews |
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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-multinews |
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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: 2.5337 |
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- Rouge1: 21.2625 |
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- Rouge2: 9.0676 |
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- Rougel: 18.6959 |
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- Rougelsum: 19.0326 |
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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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| 4.4067 | 1.0 | 1875 | 2.7776 | 20.7695 | 8.5464 | 18.4037 | 18.6862 | |
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| 3.0128 | 2.0 | 3750 | 2.6822 | 21.0579 | 8.7229 | 18.5264 | 18.832 | |
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| 2.7999 | 3.0 | 5625 | 2.5896 | 21.1361 | 8.7677 | 18.5391 | 18.8411 | |
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| 2.6794 | 4.0 | 7500 | 2.5429 | 21.2314 | 8.9749 | 18.7468 | 19.036 | |
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| 2.5963 | 5.0 | 9375 | 2.5555 | 21.2005 | 8.8569 | 18.7536 | 19.0381 | |
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| 2.5401 | 6.0 | 11250 | 2.5464 | 21.1559 | 8.9794 | 18.572 | 18.9026 | |
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| 2.5099 | 7.0 | 13125 | 2.5313 | 21.0841 | 9.0057 | 18.526 | 18.8667 | |
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| 2.488 | 8.0 | 15000 | 2.5337 | 21.2625 | 9.0676 | 18.6959 | 19.0326 | |
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### Framework versions |
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- Transformers 4.36.2 |
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- Pytorch 2.1.1+cu121 |
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- Datasets 2.16.0 |
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- Tokenizers 0.15.0 |
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