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--- |
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library_name: transformers |
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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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datasets: |
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- samsum |
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metrics: |
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- rouge |
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model-index: |
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- name: 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: samsum |
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type: samsum |
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config: samsum |
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split: validation |
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args: samsum |
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metrics: |
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- name: Rouge1 |
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type: rouge |
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value: 0.4303256962227823 |
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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 |
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This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the samsum dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.7974 |
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- Rouge1: 0.4303 |
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- Rouge2: 0.2038 |
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- Rougel: 0.3736 |
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- Rougelsum: 0.3734 |
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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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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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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| 2.1585 | 1.0 | 1842 | 1.9205 | 0.4074 | 0.1838 | 0.3517 | 0.3518 | |
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| 2.1545 | 2.0 | 3684 | 1.8882 | 0.4120 | 0.1914 | 0.3592 | 0.3588 | |
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| 2.0888 | 3.0 | 5526 | 1.8290 | 0.4196 | 0.1939 | 0.3603 | 0.3601 | |
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| 2.0272 | 4.0 | 7368 | 1.8269 | 0.4215 | 0.1975 | 0.3637 | 0.3635 | |
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| 1.9871 | 5.0 | 9210 | 1.8224 | 0.4231 | 0.1943 | 0.3634 | 0.3633 | |
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| 1.9535 | 6.0 | 11052 | 1.8055 | 0.4285 | 0.2030 | 0.3715 | 0.3715 | |
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| 1.9322 | 7.0 | 12894 | 1.7954 | 0.4270 | 0.2018 | 0.3698 | 0.3697 | |
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| 1.9181 | 8.0 | 14736 | 1.7974 | 0.4303 | 0.2038 | 0.3736 | 0.3734 | |
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### Framework versions |
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- Transformers 4.47.0 |
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- Pytorch 2.5.1+cu121 |
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- Datasets 3.2.0 |
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- Tokenizers 0.21.0 |
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