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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-cs-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: cs |
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split: test |
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args: cs |
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metrics: |
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- name: Rouge1 |
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type: rouge |
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value: 14.7738 |
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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-cs-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: 2.6706 |
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- Rouge1: 14.7738 |
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- Rouge2: 4.1406 |
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- Rougel: 13.0515 |
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- Rougelsum: 14.3388 |
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# Baseline LEAD-64 |
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- Rouge1: 21.28 |
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- Rouge2: 4.55 |
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- Rougel: 12.97 |
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- Rougelsum: 12.98 |
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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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| 5.8493 | 1.0 | 609 | 2.7949 | 12.8232 | 3.3348 | 11.0312 | 12.4584 | |
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| 3.701 | 2.0 | 1218 | 2.6966 | 14.6541 | 4.0724 | 12.9018 | 14.2196 | |
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| 3.546 | 3.0 | 1827 | 2.6706 | 14.7738 | 4.1406 | 13.0515 | 14.3388 | |
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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 |
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