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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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metrics: |
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- rouge |
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model-index: |
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- name: T5-small-summarization |
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results: [] |
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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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# T5-small-summarization |
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This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the truncated version of Samsum dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.9294 |
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- Rouge1: 0.3772 |
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- Rouge2: 0.1453 |
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- Rougel: 0.3105 |
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- Rougelsum: 0.3106 |
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- Gen Len: 16.1832 |
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## Model description |
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This model performs the summarization of Texts. |
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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: 32 |
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- eval_batch_size: 32 |
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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: 10 |
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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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| No log | 1.0 | 63 | 2.1165 | 0.338 | 0.1186 | 0.2811 | 0.2813 | 16.7595 | |
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| No log | 2.0 | 126 | 2.0210 | 0.3612 | 0.1338 | 0.2982 | 0.2985 | 16.5592 | |
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| No log | 3.0 | 189 | 1.9838 | 0.3652 | 0.1384 | 0.3034 | 0.304 | 16.1197 | |
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| No log | 4.0 | 252 | 1.9623 | 0.3715 | 0.142 | 0.3077 | 0.3079 | 16.2308 | |
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| No log | 5.0 | 315 | 1.9513 | 0.3727 | 0.1441 | 0.308 | 0.3084 | 16.1453 | |
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| No log | 6.0 | 378 | 1.9419 | 0.375 | 0.1438 | 0.309 | 0.3093 | 16.2234 | |
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| No log | 7.0 | 441 | 1.9376 | 0.3748 | 0.144 | 0.3102 | 0.3104 | 16.1465 | |
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| 2.2452 | 8.0 | 504 | 1.9324 | 0.3754 | 0.1451 | 0.3098 | 0.3099 | 16.1893 | |
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| 2.2452 | 9.0 | 567 | 1.9302 | 0.3769 | 0.1459 | 0.3112 | 0.3113 | 16.1966 | |
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| 2.2452 | 10.0 | 630 | 1.9294 | 0.3772 | 0.1453 | 0.3105 | 0.3106 | 16.1832 | |
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### Framework versions |
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- Transformers 4.37.0 |
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- Pytorch 2.1.2 |
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- Datasets 2.1.0 |
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- Tokenizers 0.15.1 |
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