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# meQ_model

This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1869
- Rouge1: 0.4942
- Rouge2: 0.346
- Rougel: 0.4743
- Rougelsum: 0.474
- Gen Len: 13.61

## 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: 2e-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
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 2.835         | 1.0   | 57   | 2.0475          | 0.2345 | 0.0895 | 0.2074 | 0.2067    | 16.82   |
| 2.3806        | 2.0   | 114  | 1.7243          | 0.2854 | 0.126  | 0.2649 | 0.2667    | 15.83   |
| 2.1701        | 3.0   | 171  | 1.5659          | 0.3633 | 0.211  | 0.3445 | 0.3444    | 14.72   |
| 2.0194        | 4.0   | 228  | 1.4690          | 0.4301 | 0.2752 | 0.4115 | 0.4127    | 13.95   |
| 1.9218        | 5.0   | 285  | 1.4159          | 0.468  | 0.3125 | 0.4499 | 0.4493    | 13.26   |
| 1.8645        | 6.0   | 342  | 1.3811          | 0.487  | 0.3462 | 0.472  | 0.4715    | 13.22   |
| 1.8254        | 7.0   | 399  | 1.3494          | 0.4836 | 0.3424 | 0.4668 | 0.466     | 13.17   |
| 1.7843        | 8.0   | 456  | 1.3277          | 0.4818 | 0.3444 | 0.4676 | 0.4672    | 13.04   |
| 1.7543        | 9.0   | 513  | 1.3084          | 0.4775 | 0.3412 | 0.463  | 0.4627    | 13.15   |
| 1.7206        | 10.0  | 570  | 1.2961          | 0.476  | 0.3393 | 0.4602 | 0.4617    | 13.13   |
| 1.6977        | 11.0  | 627  | 1.2823          | 0.4762 | 0.3395 | 0.4603 | 0.462     | 13.18   |
| 1.6725        | 12.0  | 684  | 1.2701          | 0.4841 | 0.3437 | 0.4677 | 0.4694    | 13.28   |
| 1.6479        | 13.0  | 741  | 1.2649          | 0.4912 | 0.3505 | 0.4755 | 0.4778    | 13.37   |
| 1.6313        | 14.0  | 798  | 1.2546          | 0.4896 | 0.344  | 0.4724 | 0.4742    | 13.47   |
| 1.6154        | 15.0  | 855  | 1.2488          | 0.4898 | 0.3456 | 0.4738 | 0.476     | 13.48   |
| 1.5932        | 16.0  | 912  | 1.2433          | 0.4935 | 0.3506 | 0.4776 | 0.4806    | 13.47   |
| 1.5716        | 17.0  | 969  | 1.2347          | 0.4984 | 0.3529 | 0.4789 | 0.4815    | 13.46   |
| 1.5523        | 18.0  | 1026 | 1.2314          | 0.4881 | 0.3456 | 0.4713 | 0.4722    | 13.48   |
| 1.5393        | 19.0  | 1083 | 1.2277          | 0.4925 | 0.35   | 0.4754 | 0.4761    | 13.57   |
| 1.535         | 20.0  | 1140 | 1.2239          | 0.4866 | 0.3415 | 0.4693 | 0.4708    | 13.63   |
| 1.5389        | 21.0  | 1197 | 1.2178          | 0.4785 | 0.3359 | 0.463  | 0.4621    | 13.56   |
| 1.5203        | 22.0  | 1254 | 1.2132          | 0.4837 | 0.3362 | 0.4679 | 0.4682    | 13.75   |
| 1.4909        | 23.0  | 1311 | 1.2098          | 0.4877 | 0.3393 | 0.4716 | 0.4719    | 13.71   |
| 1.4957        | 24.0  | 1368 | 1.2102          | 0.4874 | 0.3393 | 0.4713 | 0.4714    | 13.66   |
| 1.4746        | 25.0  | 1425 | 1.2076          | 0.4881 | 0.3398 | 0.4725 | 0.4717    | 13.66   |
| 1.4745        | 26.0  | 1482 | 1.2041          | 0.496  | 0.3474 | 0.4799 | 0.4792    | 13.64   |
| 1.4605        | 27.0  | 1539 | 1.2040          | 0.4903 | 0.3416 | 0.4741 | 0.4733    | 13.65   |
| 1.4465        | 28.0  | 1596 | 1.2024          | 0.4961 | 0.3461 | 0.4793 | 0.4784    | 13.7    |
| 1.4398        | 29.0  | 1653 | 1.2006          | 0.4859 | 0.3385 | 0.4692 | 0.4698    | 13.65   |
| 1.4469        | 30.0  | 1710 | 1.1976          | 0.4887 | 0.3426 | 0.473  | 0.4718    | 13.69   |
| 1.4218        | 31.0  | 1767 | 1.1965          | 0.4934 | 0.3469 | 0.4778 | 0.4764    | 13.64   |
| 1.4315        | 32.0  | 1824 | 1.1966          | 0.488  | 0.3447 | 0.4726 | 0.472     | 13.51   |
| 1.4282        | 33.0  | 1881 | 1.1957          | 0.488  | 0.3447 | 0.4726 | 0.472     | 13.51   |
| 1.396         | 34.0  | 1938 | 1.1932          | 0.489  | 0.3459 | 0.4739 | 0.4729    | 13.52   |
| 1.4028        | 35.0  | 1995 | 1.1941          | 0.4892 | 0.3434 | 0.4723 | 0.4722    | 13.63   |
| 1.4068        | 36.0  | 2052 | 1.1922          | 0.4895 | 0.347  | 0.4733 | 0.4722    | 13.57   |
| 1.3831        | 37.0  | 2109 | 1.1911          | 0.4927 | 0.3451 | 0.4742 | 0.474     | 13.63   |
| 1.3781        | 38.0  | 2166 | 1.1903          | 0.4896 | 0.3434 | 0.4717 | 0.4714    | 13.57   |
| 1.3867        | 39.0  | 2223 | 1.1889          | 0.4915 | 0.3464 | 0.4736 | 0.4729    | 13.63   |
| 1.3694        | 40.0  | 2280 | 1.1893          | 0.492  | 0.3444 | 0.4728 | 0.4723    | 13.58   |
| 1.3912        | 41.0  | 2337 | 1.1891          | 0.4902 | 0.3448 | 0.4719 | 0.4713    | 13.46   |
| 1.3793        | 42.0  | 2394 | 1.1886          | 0.492  | 0.3444 | 0.4728 | 0.4723    | 13.58   |
| 1.3664        | 43.0  | 2451 | 1.1884          | 0.4907 | 0.3434 | 0.4717 | 0.4714    | 13.53   |
| 1.3787        | 44.0  | 2508 | 1.1874          | 0.4919 | 0.3442 | 0.4725 | 0.472     | 13.61   |
| 1.3692        | 45.0  | 2565 | 1.1871          | 0.4919 | 0.3442 | 0.4725 | 0.472     | 13.61   |
| 1.3732        | 46.0  | 2622 | 1.1875          | 0.492  | 0.3444 | 0.4728 | 0.4723    | 13.58   |
| 1.3752        | 47.0  | 2679 | 1.1872          | 0.4942 | 0.346  | 0.4743 | 0.474     | 13.61   |
| 1.3581        | 48.0  | 2736 | 1.1871          | 0.4942 | 0.346  | 0.4743 | 0.474     | 13.61   |
| 1.3509        | 49.0  | 2793 | 1.1869          | 0.4942 | 0.346  | 0.4743 | 0.474     | 13.61   |
| 1.3752        | 50.0  | 2850 | 1.1869          | 0.4942 | 0.346  | 0.4743 | 0.474     | 13.61   |


### Framework versions

- Transformers 4.27.4
- Pytorch 1.13.1+cu116
- Datasets 2.11.0
- Tokenizers 0.13.2

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["rouge"], "model-index": [{"name": "meQ_model", "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 

meQ\_model
==========


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


* Loss: 1.1869
* Rouge1: 0.4942
* Rouge2: 0.346
* Rougel: 0.4743
* Rougelsum: 0.474
* Gen Len: 13.61


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: 2e-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
* num\_epochs: 50


### Training results



### Framework versions


* Transformers 4.27.4
* Pytorch 1.13.1+cu116
* Datasets 2.11.0
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-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
* num\_epochs: 50 ### Training results ### Framework versions


* Transformers 4.27.4
* Pytorch 1.13.1+cu116
* Datasets 2.11.0
* Tokenizers 0.13.2
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: 2e-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
* num\_epochs: 50 ### Training results ### Framework versions


* Transformers 4.27.4
* Pytorch 1.13.1+cu116
* Datasets 2.11.0
* Tokenizers 0.13.2
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: 2e-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
* num\_epochs: 50### Training results### Framework versions


* Transformers 4.27.4
* Pytorch 1.13.1+cu116
* Datasets 2.11.0
* Tokenizers 0.13.2