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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: 2.6303 |
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- Rouge1: 0.2243 |
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- Rouge2: 0.0638 |
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- Rougel: 0.1869 |
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- Rougelsum: 0.1873 |
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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: 0.0001 |
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- train_batch_size: 16 |
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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: 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 | 3 | 2.8417 | 0.2288 | 0.0874 | 0.2003 | 0.2016 | |
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| No log | 2.0 | 6 | 2.7634 | 0.2271 | 0.0883 | 0.1977 | 0.1967 | |
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| No log | 3.0 | 9 | 2.6403 | 0.2144 | 0.0640 | 0.1852 | 0.1853 | |
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| No log | 4.0 | 12 | 2.5802 | 0.2360 | 0.0760 | 0.2042 | 0.2060 | |
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| No log | 5.0 | 15 | 2.5559 | 0.2321 | 0.0801 | 0.2019 | 0.2022 | |
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| No log | 6.0 | 18 | 2.5504 | 0.2312 | 0.0793 | 0.2006 | 0.2028 | |
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| No log | 7.0 | 21 | 2.5511 | 0.2338 | 0.0809 | 0.2032 | 0.2055 | |
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| No log | 8.0 | 24 | 2.5562 | 0.2370 | 0.0813 | 0.2063 | 0.2078 | |
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| No log | 9.0 | 27 | 2.5584 | 0.2370 | 0.0813 | 0.2063 | 0.2078 | |
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| No log | 10.0 | 30 | 2.5568 | 0.2370 | 0.0813 | 0.2063 | 0.2078 | |
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| No log | 11.0 | 33 | 2.5600 | 0.2370 | 0.0813 | 0.2063 | 0.2078 | |
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| No log | 12.0 | 36 | 2.5662 | 0.2373 | 0.0804 | 0.1926 | 0.1910 | |
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| No log | 13.0 | 39 | 2.5772 | 0.2430 | 0.0809 | 0.1991 | 0.1996 | |
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| No log | 14.0 | 42 | 2.5900 | 0.2442 | 0.0813 | 0.1999 | 0.2005 | |
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| No log | 15.0 | 45 | 2.5993 | 0.2436 | 0.0810 | 0.1988 | 0.1995 | |
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| No log | 16.0 | 48 | 2.6078 | 0.2547 | 0.0810 | 0.2113 | 0.2128 | |
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| No log | 17.0 | 51 | 2.6174 | 0.2391 | 0.0657 | 0.2035 | 0.2027 | |
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| No log | 18.0 | 54 | 2.6243 | 0.2243 | 0.0638 | 0.1869 | 0.1873 | |
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| No log | 19.0 | 57 | 2.6285 | 0.2243 | 0.0638 | 0.1869 | 0.1873 | |
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| No log | 20.0 | 60 | 2.6303 | 0.2243 | 0.0638 | 0.1869 | 0.1873 | |
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### Framework versions |
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- Transformers 4.39.3 |
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- Pytorch 2.1.2 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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