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--- |
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license: apache-2.0 |
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base_model: google/flan-t5-large |
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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: flan-t5-large-finetuned-scope-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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# flan-t5-large-finetuned-scope-summarization |
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This model is a fine-tuned version of [google/flan-t5-large](https://huggingface.co./google/flan-t5-large) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1195 |
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- Rouge1: 24.038 |
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- Rouge2: 21.4448 |
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- Rougel: 23.6448 |
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- Rougelsum: 23.7376 |
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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: 2 |
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- eval_batch_size: 2 |
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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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| 0.3649 | 1.0 | 158 | 0.2625 | 19.5356 | 12.4535 | 16.8939 | 17.0876 | |
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| 0.2674 | 2.0 | 316 | 0.2422 | 19.7836 | 12.4864 | 16.9298 | 16.9928 | |
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| 0.2516 | 3.0 | 474 | 0.2271 | 20.4584 | 13.593 | 17.9404 | 18.0498 | |
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| 0.2407 | 4.0 | 632 | 0.2178 | 20.2729 | 13.6717 | 17.5 | 17.6375 | |
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| 0.2304 | 5.0 | 790 | 0.2087 | 20.3933 | 14.4275 | 17.9315 | 18.0607 | |
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| 0.2213 | 6.0 | 948 | 0.1969 | 21.4659 | 16.1078 | 19.4775 | 19.5604 | |
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| 0.2134 | 7.0 | 1106 | 0.1863 | 23.3097 | 19.0603 | 21.9919 | 22.1651 | |
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| 0.2069 | 8.0 | 1264 | 0.1803 | 22.5866 | 17.3665 | 20.4585 | 20.4009 | |
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| 0.2 | 9.0 | 1422 | 0.1695 | 23.7295 | 19.7783 | 22.4861 | 22.5794 | |
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| 0.1942 | 10.0 | 1580 | 0.1632 | 21.9543 | 16.572 | 19.539 | 19.5863 | |
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| 0.1883 | 11.0 | 1738 | 0.1570 | 22.5164 | 18.8651 | 21.4345 | 21.6252 | |
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| 0.1829 | 12.0 | 1896 | 0.1495 | 23.7871 | 20.6331 | 23.2495 | 23.4011 | |
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| 0.178 | 13.0 | 2054 | 0.1425 | 23.789 | 21.1006 | 23.2292 | 23.4225 | |
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| 0.1738 | 14.0 | 2212 | 0.1386 | 23.8972 | 21.2393 | 23.4578 | 23.5827 | |
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| 0.1689 | 15.0 | 2370 | 0.1331 | 23.801 | 21.2013 | 23.3414 | 23.4499 | |
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| 0.1654 | 16.0 | 2528 | 0.1286 | 24.1973 | 21.5666 | 23.7563 | 23.9153 | |
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| 0.1629 | 17.0 | 2686 | 0.1257 | 23.8243 | 21.2713 | 23.4043 | 23.4941 | |
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| 0.16 | 18.0 | 2844 | 0.1229 | 23.9496 | 21.3888 | 23.4687 | 23.6047 | |
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| 0.1578 | 19.0 | 3002 | 0.1208 | 24.009 | 21.4585 | 23.5252 | 23.646 | |
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| 0.156 | 20.0 | 3160 | 0.1195 | 24.038 | 21.4448 | 23.6448 | 23.7376 | |
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### Framework versions |
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- Transformers 4.40.1 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.19.0 |
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- Tokenizers 0.19.1 |
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