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--- |
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license: apache-2.0 |
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base_model: google/flan-t5-base |
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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: results |
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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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# results |
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This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0000 |
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- Rouge1: 0.8708 |
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- Rouge2: 0.8636 |
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- Rougel: 0.8708 |
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- Rougelsum: 0.8708 |
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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: 0.001 |
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- train_batch_size: 24 |
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- eval_batch_size: 4 |
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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: 20 |
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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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| No log | 1.0 | 1 | 1.1463 | 0.2430 | 0.1714 | 0.2430 | 0.2430 | |
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| No log | 2.0 | 2 | 0.4544 | 0.7028 | 0.6432 | 0.7028 | 0.7028 | |
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| No log | 3.0 | 3 | 0.1078 | 0.8708 | 0.8413 | 0.8708 | 0.8708 | |
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| No log | 4.0 | 4 | 0.0477 | 0.8708 | 0.8636 | 0.8708 | 0.8708 | |
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| No log | 5.0 | 5 | 0.0856 | 0.8708 | 0.8636 | 0.8708 | 0.8708 | |
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| No log | 6.0 | 6 | 0.0128 | 0.8708 | 0.8636 | 0.8708 | 0.8708 | |
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| No log | 7.0 | 7 | 0.0088 | 0.8708 | 0.8636 | 0.8708 | 0.8708 | |
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| No log | 8.0 | 8 | 0.0082 | 0.8708 | 0.8636 | 0.8708 | 0.8708 | |
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| No log | 9.0 | 9 | 0.0019 | 0.8708 | 0.8636 | 0.8708 | 0.8708 | |
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| No log | 10.0 | 10 | 0.0008 | 0.8708 | 0.8636 | 0.8708 | 0.8708 | |
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| No log | 11.0 | 11 | 0.0005 | 0.8708 | 0.8636 | 0.8708 | 0.8708 | |
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| No log | 12.0 | 12 | 0.0003 | 0.8708 | 0.8636 | 0.8708 | 0.8708 | |
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| No log | 13.0 | 13 | 0.0002 | 0.8708 | 0.8636 | 0.8708 | 0.8708 | |
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| No log | 14.0 | 14 | 0.0001 | 0.8708 | 0.8636 | 0.8708 | 0.8708 | |
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| No log | 15.0 | 15 | 0.0001 | 0.8708 | 0.8636 | 0.8708 | 0.8708 | |
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| No log | 16.0 | 16 | 0.0001 | 0.8708 | 0.8636 | 0.8708 | 0.8708 | |
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| No log | 17.0 | 17 | 0.0000 | 0.8708 | 0.8636 | 0.8708 | 0.8708 | |
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| No log | 18.0 | 18 | 0.0001 | 0.8708 | 0.8636 | 0.8708 | 0.8708 | |
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| No log | 19.0 | 19 | 0.0001 | 0.8708 | 0.8636 | 0.8708 | 0.8708 | |
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| No log | 20.0 | 20 | 0.0000 | 0.8708 | 0.8636 | 0.8708 | 0.8708 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.1 |
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