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--- |
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license: apache-2.0 |
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base_model: t5-small |
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tags: |
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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: results |
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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: 0.3967 |
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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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# results |
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This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the samsum dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4111 |
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- Rouge1: 0.3967 |
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- Rouge2: 0.1634 |
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- Rougel: 0.3272 |
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- Rougelsum: 0.3265 |
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- Gen Len: 16.6764 |
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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: 2e-05 |
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- train_batch_size: 1 |
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- eval_batch_size: 1 |
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- seed: 42 |
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- gradient_accumulation_steps: 16 |
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- total_train_batch_size: 16 |
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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: 2 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |
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|:-------------:|:------:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:| |
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| 0.4776 | 0.9992 | 920 | 0.4190 | 0.3949 | 0.1687 | 0.3315 | 0.3313 | 16.2958 | |
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| 0.4642 | 1.9984 | 1840 | 0.4140 | 0.3954 | 0.1693 | 0.3324 | 0.3326 | 16.4707 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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