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--- |
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license: apache-2.0 |
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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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- wiki_lingua |
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metrics: |
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- rouge |
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model-index: |
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- name: wiki_lingua-de-8-3-5.6e-05-mt5-small-finetuned |
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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: wiki_lingua |
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type: wiki_lingua |
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config: de |
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split: test |
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args: de |
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metrics: |
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- name: Rouge1 |
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type: rouge |
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value: 15.2299 |
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language: |
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- de |
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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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# wiki_lingua-de-8-3-5.6e-05-mt5-small-finetuned |
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This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the wiki_lingua dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.4218 |
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- Rouge1: 15.2299 |
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- Rouge2: 4.4912 |
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- Rougel: 13.4991 |
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- Rougelsum: 14.9193 |
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# Baseline LEAD64 |
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- Rouge1: 18.76 |
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- Rouge2: 4.22 |
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- Rougel: 12.14 |
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- Rougelsum: 12.14 |
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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: 3 |
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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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| 3.5656 | 1.0 | 4939 | 2.5421 | 14.4738 | 4.064 | 12.7061 | 14.1813 | |
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| 2.9444 | 2.0 | 9878 | 2.4492 | 14.8349 | 4.3457 | 13.16 | 14.5623 | |
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| 2.8378 | 3.0 | 14817 | 2.4218 | 15.2299 | 4.4912 | 13.4991 | 14.9193 | |
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### Framework versions |
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- Transformers 4.27.4 |
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- Pytorch 1.13.0 |
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- Datasets 2.1.0 |
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- Tokenizers 0.13.2 |
