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# t5-small-finetuned-wikihow_3epoch

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: 2.5163
- Rouge1: 25.5784
- Rouge2: 8.9929
- Rougel: 21.5345
- Rougelsum: 24.9382
- Gen Len: 18.384

## 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: 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 |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:|
| 2.9421        | 0.25  | 5000  | 2.6545          | 23.2336 | 7.5502 | 19.5899 | 22.5521   | 18.4076 |
| 2.8411        | 0.51  | 10000 | 2.6103          | 24.3524 | 8.2068 | 20.5238 | 23.6679   | 18.2606 |
| 2.7983        | 0.76  | 15000 | 2.5836          | 24.8169 | 8.4826 | 20.8765 | 24.1686   | 18.3211 |
| 2.7743        | 1.02  | 20000 | 2.5627          | 24.9904 | 8.5625 | 21.0344 | 24.3416   | 18.3786 |
| 2.7452        | 1.27  | 25000 | 2.5508          | 25.1497 | 8.6872 | 21.152  | 24.4751   | 18.3524 |
| 2.7353        | 1.53  | 30000 | 2.5384          | 25.2909 | 8.7408 | 21.2344 | 24.629    | 18.4453 |
| 2.7261        | 1.78  | 35000 | 2.5322          | 25.3748 | 8.7802 | 21.312  | 24.7191   | 18.3754 |
| 2.7266        | 2.03  | 40000 | 2.5265          | 25.4095 | 8.8915 | 21.3871 | 24.7685   | 18.4013 |
| 2.706         | 2.29  | 45000 | 2.5211          | 25.4372 | 8.8926 | 21.4124 | 24.7902   | 18.3776 |
| 2.7073        | 2.54  | 50000 | 2.5176          | 25.4925 | 8.9668 | 21.5103 | 24.8608   | 18.4303 |
| 2.703         | 2.8   | 55000 | 2.5163          | 25.5784 | 8.9929 | 21.5345 | 24.9382   | 18.384  |


### Framework versions

- Transformers 4.17.0
- 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", "results": [{"task": {"type": "text2text-generation", "name": "Sequence-to-sequence Language Modeling"}, "dataset": {"name": "wikihow", "type": "wikihow", "args": "all"}, "metrics": [{"type": "rouge", "value": 25.5784, "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
==================================


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


* Loss: 2.5163
* Rouge1: 25.5784
* Rouge2: 8.9929
* Rougel: 21.5345
* Rougelsum: 24.9382
* Gen Len: 18.384


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: 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 4.17.0
* Pytorch 1.10.0+cu111
* Datasets 2.0.0
* Tokenizers 0.11.6



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* 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 4.17.0
* 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: 2e-05
* 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 4.17.0
* 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: 2e-05
* 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 4.17.0
* Pytorch 1.10.0+cu111
* Datasets 2.0.0
* Tokenizers 0.11.6