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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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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_samsum_summarization_model |
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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: 39.9323 |
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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_samsum_summarization_model |
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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: 1.9328 |
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- Rouge1: 39.9323 |
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- Rouge2: 18.0293 |
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- Rougel: 34.3611 |
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- Rougelsum: 37.3087 |
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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: 14 |
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- eval_batch_size: 14 |
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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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| 4.5012 | 1.0 | 1050 | 2.1992 | 34.6608 | 14.0886 | 29.8674 | 32.1737 | |
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| 2.6852 | 2.0 | 2100 | 2.1014 | 38.1793 | 16.0747 | 32.5426 | 35.4332 | |
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| 2.4933 | 3.0 | 3150 | 2.0319 | 38.4414 | 16.4993 | 32.6973 | 35.8539 | |
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| 2.3933 | 4.0 | 4200 | 1.9910 | 39.2966 | 17.1718 | 33.5556 | 36.802 | |
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| 2.3273 | 5.0 | 5250 | 1.9764 | 39.7619 | 17.7287 | 33.9838 | 37.1345 | |
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| 2.2783 | 6.0 | 6300 | 1.9503 | 39.9351 | 17.8312 | 34.2641 | 37.2625 | |
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| 2.2543 | 7.0 | 7350 | 1.9350 | 39.9551 | 17.918 | 34.3361 | 37.2039 | |
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| 2.2383 | 8.0 | 8400 | 1.9328 | 39.9323 | 18.0293 | 34.3611 | 37.3087 | |
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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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