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# t5-small-finetuned-wikihow_3epoch_b8_lr3e-4

This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the wikihow dataset.
It achieves the following results on the evaluation set:
- Loss: 2.3136
- Rouge1: 27.3718
- Rouge2: 10.6235
- Rougel: 23.3396
- Rougelsum: 26.6889
- Gen Len: 18.5194

## 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: 0.0003
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 2.8029        | 0.25  | 5000  | 2.5368          | 25.2267 | 8.9048  | 21.2588 | 24.5804   | 18.4303 |
| 2.6924        | 0.51  | 10000 | 2.4725          | 25.6553 | 9.1904  | 21.7633 | 24.9807   | 18.5549 |
| 2.6369        | 0.76  | 15000 | 2.4332          | 26.2895 | 9.7203  | 22.3286 | 25.6009   | 18.4185 |
| 2.5994        | 1.02  | 20000 | 2.4051          | 26.1779 | 9.5708  | 22.3531 | 25.5357   | 18.561  |
| 2.521         | 1.27  | 25000 | 2.3805          | 26.7558 | 10.0411 | 22.7252 | 26.0476   | 18.304  |
| 2.5091        | 1.53  | 30000 | 2.3625          | 26.6439 | 10.0698 | 22.6662 | 25.9537   | 18.5437 |
| 2.4941        | 1.78  | 35000 | 2.3498          | 26.9322 | 10.2817 | 23.0002 | 26.2604   | 18.4953 |
| 2.4848        | 2.03  | 40000 | 2.3424          | 27.0381 | 10.3452 | 22.9749 | 26.3407   | 18.5749 |
| 2.4268        | 2.29  | 45000 | 2.3272          | 27.2386 | 10.4595 | 23.1866 | 26.5541   | 18.4954 |
| 2.4263        | 2.54  | 50000 | 2.3226          | 27.1489 | 10.532  | 23.1428 | 26.4657   | 18.5583 |
| 2.4161        | 2.8   | 55000 | 2.3136          | 27.3718 | 10.6235 | 23.3396 | 26.6889   | 18.5194 |


### Framework versions

- Transformers 4.18.0
- Pytorch 1.10.0+cu111
- Datasets 2.0.0
- Tokenizers 0.11.6

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["wikihow"], "metrics": ["rouge"], "model-index": [{"name": "t5-small-finetuned-wikihow_3epoch_b8_lr3e-4", "results": [{"task": {"type": "text2text-generation", "name": "Sequence-to-sequence Language Modeling"}, "dataset": {"name": "wikihow", "type": "wikihow", "args": "all"}, "metrics": [{"type": "rouge", "value": 27.3718, "name": "Rouge1"}]}]}]}
transformers pytorch tensorboard t5 text2text-generation generated_from_trainer dataset:wikihow license:apache-2.0 model-index autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #tensorboard #t5 #text2text-generation #generated_from_trainer #dataset-wikihow #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

t5-small-finetuned-wikihow\_3epoch\_b8\_lr3e-4
==============================================


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


* Loss: 2.3136
* Rouge1: 27.3718
* Rouge2: 10.6235
* Rougel: 23.3396
* Rougelsum: 26.6889
* Gen Len: 18.5194


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: 0.0003
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 3
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.18.0
* Pytorch 1.10.0+cu111
* Datasets 2.0.0
* Tokenizers 0.11.6



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0003
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 3
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.18.0
* Pytorch 1.10.0+cu111
* Datasets 2.0.0
* Tokenizers 0.11.6
TAGS
#transformers #pytorch #tensorboard #t5 #text2text-generation #generated_from_trainer #dataset-wikihow #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0003
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 3
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.18.0
* Pytorch 1.10.0+cu111
* Datasets 2.0.0
* Tokenizers 0.11.6
passage: TAGS
#transformers #pytorch #tensorboard #t5 #text2text-generation #generated_from_trainer #dataset-wikihow #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0003
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 3
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.18.0
* Pytorch 1.10.0+cu111
* Datasets 2.0.0
* Tokenizers 0.11.6