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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-icelandic-summary |
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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-icelandic-summary |
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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: 2.3019 |
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- Rouge1: 24.5314 |
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- Rouge2: 13.108 |
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- Rougel: 21.8551 |
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- Rougelsum: 22.5551 |
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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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| 4.2489 | 1.0 | 1914 | 2.6014 | 17.9396 | 6.9767 | 15.0632 | 15.8916 | |
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| 3.0569 | 2.0 | 3828 | 2.4547 | 21.317 | 10.0433 | 18.6257 | 19.3813 | |
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| 2.8661 | 3.0 | 5742 | 2.3843 | 23.6521 | 12.2829 | 21.0046 | 21.7077 | |
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| 2.7543 | 4.0 | 7656 | 2.3642 | 23.8878 | 12.7041 | 21.3321 | 22.0867 | |
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| 2.682 | 5.0 | 9570 | 2.3379 | 24.2206 | 12.9703 | 21.6077 | 22.3493 | |
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| 2.6276 | 6.0 | 11484 | 2.2974 | 24.5156 | 13.1087 | 21.8464 | 22.5609 | |
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| 2.588 | 7.0 | 13398 | 2.3012 | 24.7653 | 13.3338 | 22.0548 | 22.762 | |
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| 2.5723 | 8.0 | 15312 | 2.3019 | 24.5314 | 13.108 | 21.8551 | 22.5551 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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