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# t5-small-finetuned-xsum

This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the wsj_markets dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1447
- Rouge1: 10.4492
- Rouge2: 3.9563
- Rougel: 9.3368
- Rougelsum: 9.9828
- 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: 4
- eval_batch_size: 4
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:------:|:---------:|:-------:|
| 2.2742        | 1.0   | 868  | 1.3135          | 9.4644  | 2.618  | 8.4048 | 8.9764    | 19.0    |
| 1.4607        | 2.0   | 1736 | 1.2134          | 9.6327  | 3.8535 | 9.0703 | 9.2466    | 19.0    |
| 1.3579        | 3.0   | 2604 | 1.1684          | 10.1616 | 3.5498 | 9.2294 | 9.4507    | 19.0    |
| 1.3314        | 4.0   | 3472 | 1.1514          | 10.0621 | 3.6907 | 9.1635 | 9.4955    | 19.0    |
| 1.3084        | 5.0   | 4340 | 1.1447          | 10.4492 | 3.9563 | 9.3368 | 9.9828    | 19.0    |


### Framework versions

- Transformers 4.8.2
- Pytorch 1.9.0+cu102
- Datasets 1.10.0
- Tokenizers 0.10.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["wsj_markets"], "metrics": ["rouge"], "model_index": [{"name": "t5-small-finetuned-xsum", "results": [{"task": {"name": "Sequence-to-sequence Language Modeling", "type": "text2text-generation"}, "dataset": {"name": "wsj_markets", "type": "wsj_markets", "args": "default"}, "metric": {"name": "Rouge1", "type": "rouge", "value": 10.4492}}]}]}
transformers pytorch tensorboard t5 text2text-generation generated_from_trainer dataset:wsj_markets license:apache-2.0 autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #tensorboard #t5 #text2text-generation #generated_from_trainer #dataset-wsj_markets #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

t5-small-finetuned-xsum
=======================


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


* Loss: 1.1447
* Rouge1: 10.4492
* Rouge2: 3.9563
* Rougel: 9.3368
* Rougelsum: 9.9828
* 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: 4
* eval\_batch\_size: 4
* 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 4.8.2
* Pytorch 1.9.0+cu102
* Datasets 1.10.0
* Tokenizers 0.10.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 4
* eval\_batch\_size: 4
* 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 4.8.2
* Pytorch 1.9.0+cu102
* Datasets 1.10.0
* Tokenizers 0.10.3
TAGS
#transformers #pytorch #tensorboard #t5 #text2text-generation #generated_from_trainer #dataset-wsj_markets #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: 4
* eval\_batch\_size: 4
* 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 4.8.2
* Pytorch 1.9.0+cu102
* Datasets 1.10.0
* Tokenizers 0.10.3
passage: TAGS
#transformers #pytorch #tensorboard #t5 #text2text-generation #generated_from_trainer #dataset-wsj_markets #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: 4
* eval\_batch\_size: 4
* 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 4.8.2
* Pytorch 1.9.0+cu102
* Datasets 1.10.0
* Tokenizers 0.10.3