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# t5-small-finetuned-epoch15

This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4424
- Rouge1: 30.6227
- Rouge2: 18.36
- Rougel: 27.2654
- Rougelsum: 29.1342
- Gen Len: 18.9921

## 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: 15
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 1.9685        | 1.0   | 765   | 1.5842          | 29.1169 | 16.8705 | 25.8125 | 27.5815   | 18.9882 |
| 1.749         | 2.0   | 1530  | 1.5374          | 29.5968 | 17.2047 | 26.2123 | 28.0529   | 18.9948 |
| 1.7152        | 3.0   | 2295  | 1.5102          | 29.9897 | 17.6648 | 26.6741 | 28.4953   | 18.9895 |
| 1.6855        | 4.0   | 3060  | 1.4932          | 30.1755 | 17.8401 | 26.8169 | 28.6383   | 18.9928 |
| 1.6613        | 5.0   | 3825  | 1.4809          | 30.2173 | 17.8557 | 26.7923 | 28.6687   | 18.9902 |
| 1.644         | 6.0   | 4590  | 1.4716          | 30.3471 | 18.0114 | 26.9183 | 28.7556   | 18.9908 |
| 1.6306        | 7.0   | 5355  | 1.4647          | 30.3652 | 18.0496 | 26.9557 | 28.826    | 18.9915 |
| 1.6153        | 8.0   | 6120  | 1.4588          | 30.5138 | 18.2045 | 27.1705 | 29.0017   | 18.9908 |
| 1.6128        | 9.0   | 6885  | 1.4542          | 30.5644 | 18.2632 | 27.203  | 29.0705   | 18.9921 |
| 1.5992        | 10.0  | 7650  | 1.4492          | 30.5234 | 18.1797 | 27.1541 | 29.0238   | 18.9908 |
| 1.6088        | 11.0  | 8415  | 1.4461          | 30.6294 | 18.2865 | 27.2232 | 29.1328   | 18.9921 |
| 1.5933        | 12.0  | 9180  | 1.4448          | 30.5945 | 18.2752 | 27.2145 | 29.1082   | 18.9921 |
| 1.5851        | 13.0  | 9945  | 1.4431          | 30.6254 | 18.3252 | 27.2556 | 29.1329   | 18.9921 |
| 1.5869        | 14.0  | 10710 | 1.4429          | 30.5997 | 18.3426 | 27.2532 | 29.1219   | 18.9921 |
| 1.5794        | 15.0  | 11475 | 1.4424          | 30.6227 | 18.36   | 27.2654 | 29.1342   | 18.9921 |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Tokenizers 0.13.2

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["rouge"], "model-index": [{"name": "t5-small-finetuned-epoch15", "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 

t5-small-finetuned-epoch15
==========================


This model is a fine-tuned version of t5-small on an unknown dataset.
It achieves the following results on the evaluation set:


* Loss: 1.4424
* Rouge1: 30.6227
* Rouge2: 18.36
* Rougel: 27.2654
* Rougelsum: 29.1342
* Gen Len: 18.9921


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: 15
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* 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: 15
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* 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: 15
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* 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: 15
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* Tokenizers 0.13.2