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--- |
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license: apache-2.0 |
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base_model: google-t5/t5-base |
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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: t5-base-question-answer-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-base-question-answer-summarization |
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This model is a fine-tuned version of [google-t5/t5-base](https://huggingface.co/google-t5/t5-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1420 |
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- Rouge1: 87.2659 |
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- Rouge2: 79.1621 |
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- Rougel: 84.0716 |
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- Rougelsum: 84.0332 |
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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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| 0.3593 | 1.0 | 450 | 0.1339 | 87.0068 | 78.4882 | 83.5134 | 83.4528 | |
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| 0.121 | 2.0 | 900 | 0.1273 | 87.3363 | 79.1644 | 83.7472 | 83.7456 | |
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| 0.0982 | 3.0 | 1350 | 0.1314 | 87.0066 | 78.3475 | 83.0262 | 82.9739 | |
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| 0.084 | 4.0 | 1800 | 0.1322 | 87.1678 | 78.7514 | 83.4642 | 83.441 | |
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| 0.074 | 5.0 | 2250 | 0.1345 | 87.2618 | 79.114 | 83.9859 | 83.9444 | |
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| 0.0685 | 6.0 | 2700 | 0.1378 | 87.1497 | 79.0628 | 83.958 | 83.9482 | |
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| 0.0609 | 7.0 | 3150 | 0.1419 | 86.993 | 78.781 | 83.8076 | 83.7681 | |
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| 0.0591 | 8.0 | 3600 | 0.1420 | 87.2659 | 79.1621 | 84.0716 | 84.0332 | |
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### Framework versions |
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- Transformers 4.38.2 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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