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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: 38.4852 |
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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: 2.0164 |
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- Rouge1: 38.4852 |
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- Rouge2: 16.4292 |
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- Rougel: 32.9585 |
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- Rougelsum: 36.0185 |
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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: 5 |
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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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| 4.9849 | 1.0 | 1050 | 2.2071 | 34.8128 | 14.0544 | 29.8982 | 32.2776 | |
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| 2.7097 | 2.0 | 2100 | 2.1157 | 37.7348 | 15.9587 | 32.2724 | 35.2982 | |
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| 2.5305 | 3.0 | 3150 | 2.0553 | 38.4581 | 16.4518 | 32.7643 | 35.936 | |
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| 2.451 | 4.0 | 4200 | 2.0253 | 38.3972 | 16.3508 | 32.7684 | 35.9072 | |
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| 2.4132 | 5.0 | 5250 | 2.0164 | 38.4852 | 16.4292 | 32.9585 | 36.0185 | |
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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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