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# wikihow-t5-small-finetuned-pubmed

This model is a fine-tuned version of [deep-learning-analytics/wikihow-t5-small](https://huggingface.co/deep-learning-analytics/wikihow-t5-small) on the pub_med_summarization_dataset dataset.
It achieves the following results on the evaluation set:
- Loss: 2.2702
- Rouge1: 8.9619
- Rouge2: 3.2719
- Rougel: 8.1558
- Rougelsum: 8.5714
- Gen Len: 19.0

## 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: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 2.5984        | 1.0   | 4000  | 2.3696          | 10.237 | 3.8609 | 8.9776 | 9.677     | 19.0    |
| 2.5677        | 2.0   | 8000  | 2.3132          | 9.302  | 3.4499 | 8.3816 | 8.8831    | 19.0    |
| 2.5038        | 3.0   | 12000 | 2.2884          | 9.0578 | 3.3103 | 8.23   | 8.6723    | 19.0    |
| 2.4762        | 4.0   | 16000 | 2.2758          | 9.0001 | 3.2882 | 8.1845 | 8.6084    | 19.0    |
| 2.4393        | 5.0   | 20000 | 2.2702          | 8.9619 | 3.2719 | 8.1558 | 8.5714    | 19.0    |


### Framework versions

- Transformers 4.17.0
- Pytorch 1.10.0+cu111
- Datasets 1.18.3
- Tokenizers 0.11.6

{"tags": ["generated_from_trainer"], "datasets": ["pub_med_summarization_dataset"], "metrics": ["rouge"], "model-index": [{"name": "wikihow-t5-small-finetuned-pubmed", "results": [{"task": {"type": "text2text-generation", "name": "Sequence-to-sequence Language Modeling"}, "dataset": {"name": "pub_med_summarization_dataset", "type": "pub_med_summarization_dataset", "args": "document"}, "metrics": [{"type": "rouge", "value": 8.9619, "name": "Rouge1"}]}]}]}
transformers pytorch tensorboard t5 text2text-generation generated_from_trainer dataset:pub_med_summarization_dataset model-index autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #tensorboard #t5 #text2text-generation #generated_from_trainer #dataset-pub_med_summarization_dataset #model-index #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

wikihow-t5-small-finetuned-pubmed
=================================


This model is a fine-tuned version of deep-learning-analytics/wikihow-t5-small on the pub\_med\_summarization\_dataset dataset.
It achieves the following results on the evaluation set:


* Loss: 2.2702
* Rouge1: 8.9619
* Rouge2: 3.2719
* Rougel: 8.1558
* Rougelsum: 8.5714
* Gen Len: 19.0


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: 2
* eval\_batch\_size: 2
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 5
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.17.0
* Pytorch 1.10.0+cu111
* Datasets 1.18.3
* Tokenizers 0.11.6



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 2
* eval\_batch\_size: 2
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 5
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.17.0
* Pytorch 1.10.0+cu111
* Datasets 1.18.3
* Tokenizers 0.11.6
TAGS
#transformers #pytorch #tensorboard #t5 #text2text-generation #generated_from_trainer #dataset-pub_med_summarization_dataset #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: 2
* eval\_batch\_size: 2
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 5
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.17.0
* Pytorch 1.10.0+cu111
* Datasets 1.18.3
* Tokenizers 0.11.6
passage: TAGS
#transformers #pytorch #tensorboard #t5 #text2text-generation #generated_from_trainer #dataset-pub_med_summarization_dataset #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: 2
* eval\_batch\_size: 2
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 5
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.17.0
* Pytorch 1.10.0+cu111
* Datasets 1.18.3
* Tokenizers 0.11.6