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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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- mlsum |
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metrics: |
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- rouge |
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base_model: google/mt5-small |
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model-index: |
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- name: mt5-small-test-ged-mlsum_max_target_length_10 |
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results: |
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- task: |
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type: text2text-generation |
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name: Sequence-to-sequence Language Modeling |
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dataset: |
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name: mlsum |
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type: mlsum |
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args: es |
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metrics: |
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- type: rouge |
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value: 74.8229 |
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name: Rouge1 |
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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-test-ged-mlsum_max_target_length_10 |
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This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the mlsum dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3341 |
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- Rouge1: 74.8229 |
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- Rouge2: 68.1808 |
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- Rougel: 74.8297 |
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- Rougelsum: 74.8414 |
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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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| 0.5565 | 1.0 | 33296 | 0.3827 | 69.9041 | 62.821 | 69.8709 | 69.8924 | |
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| 0.2636 | 2.0 | 66592 | 0.3552 | 72.0701 | 65.4937 | 72.0787 | 72.091 | |
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| 0.2309 | 3.0 | 99888 | 0.3525 | 72.5071 | 65.8026 | 72.5132 | 72.512 | |
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| 0.2109 | 4.0 | 133184 | 0.3346 | 74.0842 | 67.4776 | 74.0887 | 74.0968 | |
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| 0.1972 | 5.0 | 166480 | 0.3398 | 74.6051 | 68.6024 | 74.6177 | 74.6365 | |
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| 0.1867 | 6.0 | 199776 | 0.3283 | 74.9022 | 68.2146 | 74.9023 | 74.926 | |
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| 0.1785 | 7.0 | 233072 | 0.3325 | 74.8631 | 68.2468 | 74.8843 | 74.9026 | |
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| 0.1725 | 8.0 | 266368 | 0.3341 | 74.8229 | 68.1808 | 74.8297 | 74.8414 | |
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### Framework versions |
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- Transformers 4.20.0 |
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- Pytorch 1.11.0+cu113 |
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- Datasets 2.3.2 |
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- Tokenizers 0.12.1 |
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