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# flan-t5-base-productdomain_instructions

This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.7837
- Rouge1: 36.5991
- Rouge2: 15.4799
- Rougel: 34.4037
- Rougelsum: 35.4543
- Gen Len: 14.0723

## 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: 5e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 100

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| No log        | 1.0   | 42   | 2.0081          | 33.7683 | 13.3348 | 31.7464 | 32.3501   | 13.6988 |
| No log        | 2.0   | 84   | 1.9122          | 35.8931 | 14.7035 | 33.5156 | 34.4285   | 14.2771 |
| No log        | 3.0   | 126  | 1.8571          | 36.1469 | 14.7339 | 34.0229 | 34.8045   | 14.8554 |
| No log        | 4.0   | 168  | 1.8285          | 34.6911 | 13.3403 | 32.4862 | 33.4576   | 14.8916 |
| No log        | 5.0   | 210  | 1.8121          | 36.1848 | 14.3484 | 34.4051 | 35.0242   | 14.6627 |
| No log        | 6.0   | 252  | 1.7985          | 35.8217 | 14.632  | 34.0805 | 34.7598   | 14.4217 |
| No log        | 7.0   | 294  | 1.7926          | 36.7474 | 14.714  | 34.4996 | 35.471    | 14.4578 |
| No log        | 8.0   | 336  | 1.7837          | 36.5991 | 15.4799 | 34.4037 | 35.4543   | 14.0723 |
| No log        | 9.0   | 378  | 1.7868          | 38.5794 | 17.8009 | 36.3936 | 37.2854   | 14.0482 |
| No log        | 10.0  | 420  | 1.7917          | 37.186  | 16.4516 | 34.5805 | 35.5496   | 14.6867 |
| No log        | 11.0  | 462  | 1.7876          | 38.2387 | 16.8602 | 35.703  | 36.5374   | 14.3735 |
| 1.5613        | 12.0  | 504  | 1.7949          | 36.6609 | 17.1147 | 34.6186 | 35.1214   | 14.8554 |
| 1.5613        | 13.0  | 546  | 1.8045          | 38.9387 | 18.0734 | 36.7076 | 37.3858   | 14.8193 |
| 1.5613        | 14.0  | 588  | 1.8211          | 39.0697 | 16.5198 | 36.7938 | 37.3292   | 14.5663 |
| 1.5613        | 15.0  | 630  | 1.8214          | 38.2996 | 17.1678 | 36.4389 | 37.0512   | 14.8313 |
| 1.5613        | 16.0  | 672  | 1.8375          | 39.4345 | 18.0457 | 37.4487 | 38.0049   | 14.5422 |
| 1.5613        | 17.0  | 714  | 1.8668          | 36.9279 | 18.0742 | 34.8528 | 35.4754   | 14.8313 |
| 1.5613        | 18.0  | 756  | 1.8708          | 36.1653 | 17.1661 | 34.0035 | 34.7663   | 14.8795 |
| 1.5613        | 19.0  | 798  | 1.9029          | 36.9342 | 16.9662 | 34.7087 | 35.3687   | 14.7229 |
| 1.5613        | 20.0  | 840  | 1.9203          | 37.0405 | 16.51   | 34.708  | 35.4081   | 15.1446 |
| 1.5613        | 21.0  | 882  | 1.9241          | 40.1118 | 18.1251 | 37.7191 | 38.5263   | 14.7590 |
| 1.5613        | 22.0  | 924  | 1.9595          | 40.3279 | 17.7924 | 38.1031 | 38.6966   | 14.9036 |
| 1.5613        | 23.0  | 966  | 1.9486          | 38.5332 | 16.3386 | 36.3524 | 36.8476   | 15.1084 |
| 0.9347        | 24.0  | 1008 | 1.9651          | 39.0175 | 17.4398 | 36.7802 | 37.3691   | 14.6386 |
| 0.9347        | 25.0  | 1050 | 2.0215          | 37.3542 | 16.7397 | 35.1152 | 35.5948   | 15.1807 |
| 0.9347        | 26.0  | 1092 | 2.0136          | 36.1433 | 16.0566 | 33.5195 | 34.1703   | 15.3855 |
| 0.9347        | 27.0  | 1134 | 2.0317          | 37.365  | 17.3246 | 34.9103 | 35.5618   | 14.7229 |
| 0.9347        | 28.0  | 1176 | 2.0574          | 38.9994 | 18.9331 | 36.8122 | 37.2818   | 14.7590 |
| 0.9347        | 29.0  | 1218 | 2.0975          | 38.704  | 17.6156 | 36.4166 | 36.855    | 15.0843 |
| 0.9347        | 30.0  | 1260 | 2.1182          | 36.6657 | 17.2754 | 34.1387 | 34.5188   | 15.3735 |
| 0.9347        | 31.0  | 1302 | 2.1353          | 38.3665 | 17.6706 | 36.2971 | 36.9008   | 14.6386 |
| 0.9347        | 32.0  | 1344 | 2.1583          | 36.461  | 15.951  | 34.1126 | 34.7238   | 14.9639 |
| 0.9347        | 33.0  | 1386 | 2.1628          | 38.2005 | 17.8068 | 35.9379 | 36.4597   | 14.8554 |
| 0.9347        | 34.0  | 1428 | 2.1632          | 38.1226 | 17.8223 | 35.7166 | 36.3522   | 15.0964 |
| 0.9347        | 35.0  | 1470 | 2.1993          | 38.1793 | 16.4788 | 36.4238 | 36.8716   | 14.6145 |
| 0.6306        | 36.0  | 1512 | 2.2278          | 37.5943 | 18.0919 | 35.9979 | 36.0291   | 14.7108 |
| 0.6306        | 37.0  | 1554 | 2.2547          | 36.7207 | 16.675  | 34.9107 | 35.0798   | 14.7229 |
| 0.6306        | 38.0  | 1596 | 2.2688          | 36.9936 | 15.8314 | 35.4724 | 35.5883   | 14.4940 |
| 0.6306        | 39.0  | 1638 | 2.3119          | 37.5208 | 16.6074 | 35.8717 | 36.445    | 14.3253 |
| 0.6306        | 40.0  | 1680 | 2.3154          | 37.8128 | 16.9579 | 35.6907 | 36.1893   | 14.6867 |
| 0.6306        | 41.0  | 1722 | 2.3531          | 39.4845 | 17.5286 | 37.8577 | 38.3204   | 14.4458 |
| 0.6306        | 42.0  | 1764 | 2.3323          | 38.4761 | 17.295  | 36.6386 | 36.9557   | 14.6145 |
| 0.6306        | 43.0  | 1806 | 2.3743          | 38.7443 | 19.2581 | 37.1116 | 37.5985   | 14.5181 |
| 0.6306        | 44.0  | 1848 | 2.4311          | 40.3561 | 18.693  | 38.8656 | 39.3105   | 14.4337 |
| 0.6306        | 45.0  | 1890 | 2.3959          | 40.0522 | 19.397  | 38.6949 | 39.2113   | 14.3494 |
| 0.6306        | 46.0  | 1932 | 2.4536          | 38.2892 | 17.2512 | 36.3746 | 37.0066   | 14.3133 |
| 0.6306        | 47.0  | 1974 | 2.4263          | 40.1626 | 18.1146 | 38.2934 | 39.0442   | 14.5422 |
| 0.4555        | 48.0  | 2016 | 2.4762          | 38.6619 | 17.2921 | 36.7469 | 37.3807   | 14.3614 |
| 0.4555        | 49.0  | 2058 | 2.5072          | 38.2839 | 17.8954 | 36.532  | 36.9102   | 14.5181 |
| 0.4555        | 50.0  | 2100 | 2.5133          | 39.5629 | 18.1928 | 37.5546 | 38.2356   | 14.4578 |
| 0.4555        | 51.0  | 2142 | 2.5239          | 39.6734 | 17.4027 | 37.8029 | 38.0765   | 14.3253 |
| 0.4555        | 52.0  | 2184 | 2.5491          | 39.6165 | 18.1724 | 37.5788 | 38.5066   | 14.4578 |
| 0.4555        | 53.0  | 2226 | 2.5733          | 38.1501 | 18.2663 | 36.3533 | 37.0174   | 14.8554 |
| 0.4555        | 54.0  | 2268 | 2.5716          | 36.2353 | 16.133  | 34.1902 | 34.7408   | 14.7590 |
| 0.4555        | 55.0  | 2310 | 2.6192          | 37.8879 | 17.7186 | 35.9678 | 36.6746   | 14.9036 |
| 0.4555        | 56.0  | 2352 | 2.6474          | 37.1621 | 17.0886 | 35.4221 | 35.731    | 14.5181 |
| 0.4555        | 57.0  | 2394 | 2.6623          | 37.5523 | 16.7998 | 35.4469 | 36.0076   | 14.4699 |
| 0.4555        | 58.0  | 2436 | 2.6607          | 38.0032 | 17.0229 | 36.1551 | 36.5535   | 14.1807 |
| 0.4555        | 59.0  | 2478 | 2.7150          | 38.1025 | 17.4752 | 36.5283 | 36.7015   | 14.2289 |
| 0.3508        | 60.0  | 2520 | 2.6941          | 39.797  | 19.2379 | 38.1214 | 38.2261   | 14.3614 |
| 0.3508        | 61.0  | 2562 | 2.7107          | 38.8625 | 17.623  | 36.6963 | 37.0603   | 14.1325 |
| 0.3508        | 62.0  | 2604 | 2.6814          | 37.5211 | 16.4479 | 35.5462 | 35.8889   | 14.3494 |
| 0.3508        | 63.0  | 2646 | 2.7484          | 38.6866 | 17.6612 | 36.7428 | 37.1636   | 14.0723 |
| 0.3508        | 64.0  | 2688 | 2.7395          | 38.0483 | 17.6948 | 36.2878 | 36.697    | 14.1807 |
| 0.3508        | 65.0  | 2730 | 2.7365          | 37.6712 | 17.2705 | 35.8893 | 36.3441   | 14.4458 |
| 0.3508        | 66.0  | 2772 | 2.7555          | 37.9902 | 17.7247 | 36.0837 | 36.7237   | 14.3012 |
| 0.3508        | 67.0  | 2814 | 2.7494          | 36.6603 | 16.2134 | 34.6886 | 35.287    | 14.5783 |
| 0.3508        | 68.0  | 2856 | 2.7826          | 37.4075 | 16.5272 | 35.4471 | 35.8108   | 14.4458 |
| 0.3508        | 69.0  | 2898 | 2.7913          | 37.5132 | 16.5865 | 35.5267 | 35.8753   | 14.3133 |
| 0.3508        | 70.0  | 2940 | 2.8110          | 38.0779 | 17.5734 | 36.2356 | 36.4576   | 14.1687 |
| 0.3508        | 71.0  | 2982 | 2.8468          | 38.0068 | 17.1148 | 35.834  | 36.2888   | 14.2289 |
| 0.2859        | 72.0  | 3024 | 2.8722          | 37.0923 | 17.2183 | 35.4736 | 35.5467   | 14.2048 |
| 0.2859        | 73.0  | 3066 | 2.8532          | 37.3506 | 17.381  | 35.5293 | 35.7809   | 14.1928 |
| 0.2859        | 74.0  | 3108 | 2.8052          | 36.9958 | 16.5001 | 35.0384 | 35.4851   | 14.3735 |
| 0.2859        | 75.0  | 3150 | 2.8523          | 37.1479 | 15.9411 | 35.287  | 35.7899   | 14.3855 |
| 0.2859        | 76.0  | 3192 | 2.8778          | 36.8889 | 15.6829 | 34.905  | 35.3649   | 14.4337 |
| 0.2859        | 77.0  | 3234 | 2.9079          | 36.5824 | 15.5738 | 34.6425 | 35.1927   | 14.3614 |
| 0.2859        | 78.0  | 3276 | 2.8787          | 36.1728 | 15.938  | 34.4013 | 34.8261   | 14.4819 |
| 0.2859        | 79.0  | 3318 | 2.9080          | 35.9696 | 15.6976 | 34.2352 | 34.5983   | 14.6386 |
| 0.2859        | 80.0  | 3360 | 2.8772          | 37.0747 | 16.8528 | 35.1818 | 35.5885   | 14.4217 |
| 0.2859        | 81.0  | 3402 | 2.9020          | 36.3635 | 17.4462 | 34.3583 | 34.9417   | 14.4819 |
| 0.2859        | 82.0  | 3444 | 2.8993          | 37.4704 | 17.335  | 35.6702 | 36.1192   | 14.4217 |
| 0.2859        | 83.0  | 3486 | 2.8920          | 37.1973 | 17.3126 | 35.4618 | 35.8107   | 14.5542 |
| 0.2455        | 84.0  | 3528 | 2.9112          | 37.3907 | 17.2948 | 35.5391 | 35.9917   | 14.5783 |
| 0.2455        | 85.0  | 3570 | 2.9250          | 36.3332 | 16.2698 | 34.4579 | 34.7125   | 14.4337 |
| 0.2455        | 86.0  | 3612 | 2.9090          | 37.8226 | 17.3181 | 35.8265 | 36.4089   | 14.2048 |
| 0.2455        | 87.0  | 3654 | 2.9097          | 37.5181 | 17.2305 | 35.5447 | 35.9105   | 14.4940 |
| 0.2455        | 88.0  | 3696 | 2.9120          | 36.5995 | 16.6394 | 34.8092 | 35.1975   | 14.6867 |
| 0.2455        | 89.0  | 3738 | 2.9235          | 37.3048 | 16.939  | 35.3615 | 35.741    | 14.4578 |
| 0.2455        | 90.0  | 3780 | 2.9270          | 37.6118 | 17.4867 | 35.656  | 36.0439   | 14.6145 |
| 0.2455        | 91.0  | 3822 | 2.9260          | 37.6441 | 17.5091 | 35.7376 | 36.113    | 14.4578 |
| 0.2455        | 92.0  | 3864 | 2.9432          | 37.4994 | 17.3906 | 35.593  | 35.977    | 14.2651 |
| 0.2455        | 93.0  | 3906 | 2.9525          | 37.3703 | 17.3245 | 35.4908 | 35.9012   | 14.5663 |
| 0.2455        | 94.0  | 3948 | 2.9546          | 36.9876 | 17.1669 | 35.1814 | 35.5809   | 14.5542 |
| 0.2455        | 95.0  | 3990 | 2.9584          | 37.1337 | 17.1325 | 35.3505 | 35.6894   | 14.5542 |
| 0.2247        | 96.0  | 4032 | 2.9607          | 36.8183 | 16.9985 | 35.0273 | 35.3368   | 14.6024 |
| 0.2247        | 97.0  | 4074 | 2.9630          | 36.8418 | 17.027  | 35.0511 | 35.3509   | 14.6145 |
| 0.2247        | 98.0  | 4116 | 2.9610          | 36.8814 | 17.027  | 35.1067 | 35.4699   | 14.5663 |
| 0.2247        | 99.0  | 4158 | 2.9581          | 36.8814 | 17.027  | 35.1067 | 35.4699   | 14.5663 |
| 0.2247        | 100.0 | 4200 | 2.9576          | 36.8814 | 17.027  | 35.1067 | 35.4699   | 14.5663 |


### Framework versions

- Transformers 4.29.2
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["rouge"], "model-index": [{"name": "flan-t5-base-productdomain_instructions", "results": []}]}
transformers pytorch tensorboard t5 text2text-generation generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #tensorboard #t5 #text2text-generation #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

flan-t5-base-productdomain\_instructions
========================================


This model is a fine-tuned version of google/flan-t5-base on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 1.7837
* Rouge1: 36.5991
* Rouge2: 15.4799
* Rougel: 34.4037
* Rougelsum: 35.4543
* Gen Len: 14.0723


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: 5e-05
* train\_batch\_size: 16
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 100


### Training results



### Framework versions


* Transformers 4.29.2
* Pytorch 2.0.1+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 16
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 100 ### Training results ### Framework versions


* Transformers 4.29.2
* Pytorch 2.0.1+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #t5 #text2text-generation #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 16
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 100 ### Training results ### Framework versions


* Transformers 4.29.2
* Pytorch 2.0.1+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3