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	---
	license: apache-2.0
	tags:
	- generated_from_trainer
	metrics:
	- rouge
	model-index:
	- name: output
	results: []
	---

	<!-- This model card has been generated automatically according to the information the Trainer had access to. You
	should probably proofread and complete it, then remove this comment. -->

	# output

	This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on an unknown dataset.
	It achieves the following results on the evaluation set:
	- Loss: 1.1885
	- Rouge1: 65.4762
	- Rouge2: 0.0
	- Rougel: 65.4762
	- Rougelsum: 65.4762
	- Gen Len: 2.1905

	## Model description

	More information needed

	## Intended uses & limitations

	More information needed

	## Training and evaluation data

	More information needed

	## Training procedure

	### Training hyperparameters

	The following hyperparameters were used during training:
	- learning_rate: 3e-05
	- train_batch_size: 16
	- eval_batch_size: 16
	- seed: 42
	- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
	- lr_scheduler_type: linear
	- lr_scheduler_warmup_steps: 20
	- num_epochs: 50

	### Training results

	\| Training Loss \| Epoch \| Step \| Validation Loss \| Rouge1 \| Rouge2 \| Rougel \| Rougelsum \| Gen Len \|
	\|:-------------:\|:-----:\|:----:\|:---------------:\|:-------:\|:------:\|:-------:\|:---------:\|:-------:\|
	\| 1.2679 \| 1.0 \| 42 \| 1.3033 \| 48.8095 \| 0.0 \| 48.8095 \| 48.8095 \| 4.0119 \|
	\| 1.0917 \| 2.0 \| 84 \| 1.1075 \| 48.8095 \| 0.0 \| 48.8095 \| 48.8095 \| 2.2738 \|
	\| 0.8305 \| 3.0 \| 126 \| 1.0366 \| 45.2381 \| 0.0 \| 45.2381 \| 45.2381 \| 2.3095 \|
	\| 0.6058 \| 4.0 \| 168 \| 0.9865 \| 48.8095 \| 0.0 \| 48.8095 \| 48.8095 \| 2.4524 \|
	\| 0.5114 \| 5.0 \| 210 \| 0.9289 \| 55.9524 \| 0.0 \| 55.9524 \| 55.9524 \| 2.4048 \|
	\| 0.6026 \| 6.0 \| 252 \| 0.9373 \| 53.5714 \| 0.0 \| 53.5714 \| 53.5714 \| 2.3214 \|
	\| 0.6428 \| 7.0 \| 294 \| 0.8762 \| 53.5714 \| 0.0 \| 53.5714 \| 53.5714 \| 2.3095 \|
	\| 0.5375 \| 8.0 \| 336 \| 0.8908 \| 54.7619 \| 0.0 \| 54.7619 \| 54.7619 \| 2.3333 \|
	\| 0.4296 \| 9.0 \| 378 \| 0.9172 \| 50.0 \| 0.0 \| 50.0 \| 50.0 \| 2.3452 \|
	\| 0.4644 \| 10.0 \| 420 \| 0.8882 \| 60.7143 \| 0.0 \| 60.7143 \| 60.7143 \| 2.3452 \|
	\| 0.42 \| 11.0 \| 462 \| 0.8917 \| 54.7619 \| 0.0 \| 54.7619 \| 54.7619 \| 2.2619 \|
	\| 0.3727 \| 12.0 \| 504 \| 0.8710 \| 55.9524 \| 0.0 \| 55.9524 \| 55.9524 \| 2.3571 \|
	\| 0.4061 \| 13.0 \| 546 \| 0.8817 \| 54.7619 \| 0.0 \| 54.7619 \| 54.7619 \| 2.2857 \|
	\| 0.3221 \| 14.0 \| 588 \| 0.9284 \| 57.1429 \| 0.0 \| 57.1429 \| 57.1429 \| 2.2857 \|
	\| 0.3676 \| 15.0 \| 630 \| 0.9313 \| 57.1429 \| 0.0 \| 57.1429 \| 57.1429 \| 2.0476 \|
	\| 0.264 \| 16.0 \| 672 \| 0.9315 \| 59.5238 \| 0.0 \| 59.5238 \| 59.5238 \| 2.0595 \|
	\| 0.2933 \| 17.0 \| 714 \| 0.9265 \| 64.2857 \| 0.0 \| 64.2857 \| 64.2857 \| 2.1310 \|
	\| 0.2446 \| 18.0 \| 756 \| 0.9254 \| 61.9048 \| 0.0 \| 61.9048 \| 61.9048 \| 2.0714 \|
	\| 0.2356 \| 19.0 \| 798 \| 0.9390 \| 63.0952 \| 0.0 \| 63.0952 \| 63.0952 \| 2.0714 \|
	\| 0.3102 \| 20.0 \| 840 \| 0.9837 \| 61.9048 \| 0.0 \| 61.9048 \| 61.9048 \| 2.1071 \|
	\| 0.1539 \| 21.0 \| 882 \| 0.9727 \| 60.7143 \| 0.0 \| 60.7143 \| 60.7143 \| 2.0952 \|
	\| 0.1674 \| 22.0 \| 924 \| 1.0114 \| 61.9048 \| 0.0 \| 61.9048 \| 61.9048 \| 2.0952 \|
	\| 0.1831 \| 23.0 \| 966 \| 0.9869 \| 61.9048 \| 0.0 \| 61.9048 \| 61.9048 \| 2.0595 \|
	\| 0.201 \| 24.0 \| 1008 \| 0.9904 \| 60.7143 \| 0.0 \| 60.7143 \| 60.7143 \| 2.0595 \|
	\| 0.1602 \| 25.0 \| 1050 \| 0.9883 \| 60.7143 \| 0.0 \| 60.7143 \| 60.7143 \| 2.0595 \|
	\| 0.158 \| 26.0 \| 1092 \| 1.0057 \| 63.0952 \| 0.0 \| 63.0952 \| 63.0952 \| 2.1071 \|
	\| 0.1468 \| 27.0 \| 1134 \| 0.9998 \| 67.8571 \| 0.0 \| 67.8571 \| 67.8571 \| 2.1429 \|
	\| 0.109 \| 28.0 \| 1176 \| 1.0052 \| 63.0952 \| 0.0 \| 63.0952 \| 63.0952 \| 2.3333 \|
	\| 0.1397 \| 29.0 \| 1218 \| 1.0137 \| 65.4762 \| 0.0 \| 65.4762 \| 65.4762 \| 2.3333 \|
	\| 0.1204 \| 30.0 \| 1260 \| 1.0482 \| 63.0952 \| 0.0 \| 63.0952 \| 63.0952 \| 2.3452 \|
	\| 0.1577 \| 31.0 \| 1302 \| 1.0787 \| 66.6667 \| 0.0 \| 66.6667 \| 66.6667 \| 2.3452 \|
	\| 0.1112 \| 32.0 \| 1344 \| 1.0513 \| 63.0952 \| 0.0 \| 63.0952 \| 63.0952 \| 2.3452 \|
	\| 0.0932 \| 33.0 \| 1386 \| 1.0786 \| 63.0952 \| 0.0 \| 63.0952 \| 63.0952 \| 2.3452 \|
	\| 0.0989 \| 34.0 \| 1428 \| 1.1378 \| 63.0952 \| 0.0 \| 63.0952 \| 63.0952 \| 2.3452 \|
	\| 0.0858 \| 35.0 \| 1470 \| 1.1055 \| 65.4762 \| 0.0 \| 65.4762 \| 65.4762 \| 2.3452 \|
	\| 0.1056 \| 36.0 \| 1512 \| 1.1297 \| 64.2857 \| 0.0 \| 64.2857 \| 64.2857 \| 2.3571 \|
	\| 0.14 \| 37.0 \| 1554 \| 1.1604 \| 64.2857 \| 0.0 \| 64.2857 \| 64.2857 \| 2.3452 \|
	\| 0.0592 \| 38.0 \| 1596 \| 1.1213 \| 65.4762 \| 0.0 \| 65.4762 \| 65.4762 \| 2.3452 \|
	\| 0.1121 \| 39.0 \| 1638 \| 1.1489 \| 65.4762 \| 0.0 \| 65.4762 \| 65.4762 \| 2.3452 \|
	\| 0.1917 \| 40.0 \| 1680 \| 1.1544 \| 64.2857 \| 0.0 \| 64.2857 \| 64.2857 \| 2.3452 \|
	\| 0.1178 \| 41.0 \| 1722 \| 1.1561 \| 64.2857 \| 0.0 \| 64.2857 \| 64.2857 \| 2.3452 \|
	\| 0.0761 \| 42.0 \| 1764 \| 1.2013 \| 63.0952 \| 0.0 \| 63.0952 \| 63.0952 \| 2.1905 \|
	\| 0.0911 \| 43.0 \| 1806 \| 1.2075 \| 64.2857 \| 0.0 \| 64.2857 \| 64.2857 \| 2.1548 \|
	\| 0.1081 \| 44.0 \| 1848 \| 1.2134 \| 66.6667 \| 0.0 \| 66.6667 \| 66.6667 \| 2.1548 \|
	\| 0.089 \| 45.0 \| 1890 \| 1.1861 \| 64.2857 \| 0.0 \| 64.2857 \| 64.2857 \| 2.1905 \|
	\| 0.0828 \| 46.0 \| 1932 \| 1.1988 \| 65.4762 \| 0.0 \| 65.4762 \| 65.4762 \| 2.1905 \|
	\| 0.0818 \| 47.0 \| 1974 \| 1.1886 \| 64.2857 \| 0.0 \| 64.2857 \| 64.2857 \| 2.1905 \|
	\| 0.0899 \| 48.0 \| 2016 \| 1.1988 \| 64.2857 \| 0.0 \| 64.2857 \| 64.2857 \| 2.1905 \|
	\| 0.0923 \| 49.0 \| 2058 \| 1.1968 \| 65.4762 \| 0.0 \| 65.4762 \| 65.4762 \| 2.1905 \|
	\| 0.0859 \| 50.0 \| 2100 \| 1.1885 \| 65.4762 \| 0.0 \| 65.4762 \| 65.4762 \| 2.1905 \|


	### Framework versions

	- Transformers 4.26.1
	- Pytorch 1.13.1+cu117
	- Datasets 2.10.1
	- Tokenizers 0.13.2

	---
	license: apache-2.0
	tags:
	- generated_from_trainer
	metrics:
	- rouge
	model-index:
	- name: output
	results: []
	---

	<!-- This model card has been generated automatically according to the information the Trainer had access to. You
	should probably proofread and complete it, then remove this comment. -->

	# output

	This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on an unknown dataset.
	It achieves the following results on the evaluation set:
	- Loss: 1.1885
	- Rouge1: 65.4762
	- Rouge2: 0.0
	- Rougel: 65.4762
	- Rougelsum: 65.4762
	- Gen Len: 2.1905

	## Model description

	More information needed

	## Intended uses & limitations

	More information needed

	## Training and evaluation data

	More information needed

	## Training procedure

	### Training hyperparameters

	The following hyperparameters were used during training:
	- learning_rate: 3e-05
	- train_batch_size: 16
	- eval_batch_size: 16
	- seed: 42
	- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
	- lr_scheduler_type: linear
	- lr_scheduler_warmup_steps: 20
	- num_epochs: 50

	### Training results

	\| Training Loss \| Epoch \| Step \| Validation Loss \| Rouge1 \| Rouge2 \| Rougel \| Rougelsum \| Gen Len \|
	\|:-------------:\|:-----:\|:----:\|:---------------:\|:-------:\|:------:\|:-------:\|:---------:\|:-------:\|
	\| 1.2679 \| 1.0 \| 42 \| 1.3033 \| 48.8095 \| 0.0 \| 48.8095 \| 48.8095 \| 4.0119 \|
	\| 1.0917 \| 2.0 \| 84 \| 1.1075 \| 48.8095 \| 0.0 \| 48.8095 \| 48.8095 \| 2.2738 \|
	\| 0.8305 \| 3.0 \| 126 \| 1.0366 \| 45.2381 \| 0.0 \| 45.2381 \| 45.2381 \| 2.3095 \|
	\| 0.6058 \| 4.0 \| 168 \| 0.9865 \| 48.8095 \| 0.0 \| 48.8095 \| 48.8095 \| 2.4524 \|
	\| 0.5114 \| 5.0 \| 210 \| 0.9289 \| 55.9524 \| 0.0 \| 55.9524 \| 55.9524 \| 2.4048 \|
	\| 0.6026 \| 6.0 \| 252 \| 0.9373 \| 53.5714 \| 0.0 \| 53.5714 \| 53.5714 \| 2.3214 \|
	\| 0.6428 \| 7.0 \| 294 \| 0.8762 \| 53.5714 \| 0.0 \| 53.5714 \| 53.5714 \| 2.3095 \|
	\| 0.5375 \| 8.0 \| 336 \| 0.8908 \| 54.7619 \| 0.0 \| 54.7619 \| 54.7619 \| 2.3333 \|
	\| 0.4296 \| 9.0 \| 378 \| 0.9172 \| 50.0 \| 0.0 \| 50.0 \| 50.0 \| 2.3452 \|
	\| 0.4644 \| 10.0 \| 420 \| 0.8882 \| 60.7143 \| 0.0 \| 60.7143 \| 60.7143 \| 2.3452 \|
	\| 0.42 \| 11.0 \| 462 \| 0.8917 \| 54.7619 \| 0.0 \| 54.7619 \| 54.7619 \| 2.2619 \|
	\| 0.3727 \| 12.0 \| 504 \| 0.8710 \| 55.9524 \| 0.0 \| 55.9524 \| 55.9524 \| 2.3571 \|
	\| 0.4061 \| 13.0 \| 546 \| 0.8817 \| 54.7619 \| 0.0 \| 54.7619 \| 54.7619 \| 2.2857 \|
	\| 0.3221 \| 14.0 \| 588 \| 0.9284 \| 57.1429 \| 0.0 \| 57.1429 \| 57.1429 \| 2.2857 \|
	\| 0.3676 \| 15.0 \| 630 \| 0.9313 \| 57.1429 \| 0.0 \| 57.1429 \| 57.1429 \| 2.0476 \|
	\| 0.264 \| 16.0 \| 672 \| 0.9315 \| 59.5238 \| 0.0 \| 59.5238 \| 59.5238 \| 2.0595 \|
	\| 0.2933 \| 17.0 \| 714 \| 0.9265 \| 64.2857 \| 0.0 \| 64.2857 \| 64.2857 \| 2.1310 \|
	\| 0.2446 \| 18.0 \| 756 \| 0.9254 \| 61.9048 \| 0.0 \| 61.9048 \| 61.9048 \| 2.0714 \|
	\| 0.2356 \| 19.0 \| 798 \| 0.9390 \| 63.0952 \| 0.0 \| 63.0952 \| 63.0952 \| 2.0714 \|
	\| 0.3102 \| 20.0 \| 840 \| 0.9837 \| 61.9048 \| 0.0 \| 61.9048 \| 61.9048 \| 2.1071 \|
	\| 0.1539 \| 21.0 \| 882 \| 0.9727 \| 60.7143 \| 0.0 \| 60.7143 \| 60.7143 \| 2.0952 \|
	\| 0.1674 \| 22.0 \| 924 \| 1.0114 \| 61.9048 \| 0.0 \| 61.9048 \| 61.9048 \| 2.0952 \|
	\| 0.1831 \| 23.0 \| 966 \| 0.9869 \| 61.9048 \| 0.0 \| 61.9048 \| 61.9048 \| 2.0595 \|
	\| 0.201 \| 24.0 \| 1008 \| 0.9904 \| 60.7143 \| 0.0 \| 60.7143 \| 60.7143 \| 2.0595 \|
	\| 0.1602 \| 25.0 \| 1050 \| 0.9883 \| 60.7143 \| 0.0 \| 60.7143 \| 60.7143 \| 2.0595 \|
	\| 0.158 \| 26.0 \| 1092 \| 1.0057 \| 63.0952 \| 0.0 \| 63.0952 \| 63.0952 \| 2.1071 \|
	\| 0.1468 \| 27.0 \| 1134 \| 0.9998 \| 67.8571 \| 0.0 \| 67.8571 \| 67.8571 \| 2.1429 \|
	\| 0.109 \| 28.0 \| 1176 \| 1.0052 \| 63.0952 \| 0.0 \| 63.0952 \| 63.0952 \| 2.3333 \|
	\| 0.1397 \| 29.0 \| 1218 \| 1.0137 \| 65.4762 \| 0.0 \| 65.4762 \| 65.4762 \| 2.3333 \|
	\| 0.1204 \| 30.0 \| 1260 \| 1.0482 \| 63.0952 \| 0.0 \| 63.0952 \| 63.0952 \| 2.3452 \|
	\| 0.1577 \| 31.0 \| 1302 \| 1.0787 \| 66.6667 \| 0.0 \| 66.6667 \| 66.6667 \| 2.3452 \|
	\| 0.1112 \| 32.0 \| 1344 \| 1.0513 \| 63.0952 \| 0.0 \| 63.0952 \| 63.0952 \| 2.3452 \|
	\| 0.0932 \| 33.0 \| 1386 \| 1.0786 \| 63.0952 \| 0.0 \| 63.0952 \| 63.0952 \| 2.3452 \|
	\| 0.0989 \| 34.0 \| 1428 \| 1.1378 \| 63.0952 \| 0.0 \| 63.0952 \| 63.0952 \| 2.3452 \|
	\| 0.0858 \| 35.0 \| 1470 \| 1.1055 \| 65.4762 \| 0.0 \| 65.4762 \| 65.4762 \| 2.3452 \|
	\| 0.1056 \| 36.0 \| 1512 \| 1.1297 \| 64.2857 \| 0.0 \| 64.2857 \| 64.2857 \| 2.3571 \|
	\| 0.14 \| 37.0 \| 1554 \| 1.1604 \| 64.2857 \| 0.0 \| 64.2857 \| 64.2857 \| 2.3452 \|
	\| 0.0592 \| 38.0 \| 1596 \| 1.1213 \| 65.4762 \| 0.0 \| 65.4762 \| 65.4762 \| 2.3452 \|
	\| 0.1121 \| 39.0 \| 1638 \| 1.1489 \| 65.4762 \| 0.0 \| 65.4762 \| 65.4762 \| 2.3452 \|
	\| 0.1917 \| 40.0 \| 1680 \| 1.1544 \| 64.2857 \| 0.0 \| 64.2857 \| 64.2857 \| 2.3452 \|
	\| 0.1178 \| 41.0 \| 1722 \| 1.1561 \| 64.2857 \| 0.0 \| 64.2857 \| 64.2857 \| 2.3452 \|
	\| 0.0761 \| 42.0 \| 1764 \| 1.2013 \| 63.0952 \| 0.0 \| 63.0952 \| 63.0952 \| 2.1905 \|
	\| 0.0911 \| 43.0 \| 1806 \| 1.2075 \| 64.2857 \| 0.0 \| 64.2857 \| 64.2857 \| 2.1548 \|
	\| 0.1081 \| 44.0 \| 1848 \| 1.2134 \| 66.6667 \| 0.0 \| 66.6667 \| 66.6667 \| 2.1548 \|
	\| 0.089 \| 45.0 \| 1890 \| 1.1861 \| 64.2857 \| 0.0 \| 64.2857 \| 64.2857 \| 2.1905 \|
	\| 0.0828 \| 46.0 \| 1932 \| 1.1988 \| 65.4762 \| 0.0 \| 65.4762 \| 65.4762 \| 2.1905 \|
	\| 0.0818 \| 47.0 \| 1974 \| 1.1886 \| 64.2857 \| 0.0 \| 64.2857 \| 64.2857 \| 2.1905 \|
	\| 0.0899 \| 48.0 \| 2016 \| 1.1988 \| 64.2857 \| 0.0 \| 64.2857 \| 64.2857 \| 2.1905 \|
	\| 0.0923 \| 49.0 \| 2058 \| 1.1968 \| 65.4762 \| 0.0 \| 65.4762 \| 65.4762 \| 2.1905 \|
	\| 0.0859 \| 50.0 \| 2100 \| 1.1885 \| 65.4762 \| 0.0 \| 65.4762 \| 65.4762 \| 2.1905 \|


	### Framework versions

	- Transformers 4.26.1
	- Pytorch 1.13.1+cu117
	- Datasets 2.10.1
	- Tokenizers 0.13.2