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--- |
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license: apache-2.0 |
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base_model: google/flan-t5-small |
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tags: |
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- summarization |
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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: flan-t5-small-destination-inference |
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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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# flan-t5-small-destination-inference |
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This model is a fine-tuned version of [google/flan-t5-small](https://huggingface.co/google/flan-t5-small) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1533 |
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- Rouge1: 93.7111 |
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- Rouge2: 0.0 |
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- Rougel: 93.7462 |
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- Rougelsum: 93.7462 |
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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: 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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| 1.5338 | 1.0 | 5701 | 0.2460 | 89.4132 | 0.0 | 89.4395 | 89.4483 | |
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| 1.2443 | 2.0 | 11402 | 0.2024 | 90.8692 | 0.0 | 90.8868 | 90.8955 | |
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| 1.1477 | 3.0 | 17103 | 0.1810 | 91.8779 | 0.0 | 91.8954 | 91.8954 | |
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| 1.0878 | 4.0 | 22804 | 0.1693 | 92.5445 | 0.0 | 92.5621 | 92.5621 | |
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| 1.0495 | 5.0 | 28505 | 0.1609 | 93.3164 | 0.0 | 93.3427 | 93.3339 | |
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| 1.0178 | 6.0 | 34206 | 0.1556 | 93.4041 | 0.0 | 93.4216 | 93.4304 | |
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| 0.9981 | 7.0 | 39907 | 0.1542 | 93.6935 | 0.0 | 93.7286 | 93.7286 | |
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| 0.9848 | 8.0 | 45608 | 0.1533 | 93.7111 | 0.0 | 93.7462 | 93.7462 | |
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### Framework versions |
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- Transformers 4.33.3 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 2.14.5 |
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- Tokenizers 0.13.3 |
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