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# leonardo-simao/t5-small-finetuned-samsum

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:
- Train Loss: 1.7827
- Validation Loss: 1.6911
- Train Rouge1: 45.5008
- Train Rouge2: 21.8513
- Train Rougel: 37.7516
- Train Rougelsum: 41.9987
- Train Gen Len: 22.7335
- Epoch: 9

## 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:
- optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 2e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01}
- training_precision: float32

### Training results

| Train Loss | Validation Loss | Train Rouge1 | Train Rouge2 | Train Rougel | Train Rougelsum | Train Gen Len | Epoch |
|:----------:|:---------------:|:------------:|:------------:|:------------:|:---------------:|:-------------:|:-----:|
| 2.2008     | 1.8738          | 40.8957      | 17.7161      | 33.7622      | 37.8215         | 21.6076       | 0     |
| 2.0354     | 1.8199          | 42.3240      | 18.8923      | 35.2173      | 39.3636         | 22.6430       | 1     |
| 1.9740     | 1.7798          | 43.1803      | 19.4935      | 35.5992      | 39.8421         | 22.0257       | 2     |
| 1.9317     | 1.7616          | 43.6967      | 19.8639      | 36.3157      | 40.3523         | 22.8240       | 3     |
| 1.8972     | 1.7465          | 43.7177      | 20.1991      | 36.5373      | 40.6343         | 23.4181       | 4     |
| 1.8683     | 1.7279          | 44.5495      | 20.8857      | 37.0714      | 41.2688         | 23.1027       | 5     |
| 1.8467     | 1.7176          | 44.6826      | 20.8768      | 37.1247      | 41.2629         | 23.0770       | 6     |
| 1.8239     | 1.7093          | 44.8019      | 20.9512      | 37.2078      | 41.3814         | 23.4193       | 7     |
| 1.8021     | 1.7030          | 45.4762      | 21.8055      | 37.9099      | 41.9938         | 23.1064       | 8     |
| 1.7827     | 1.6911          | 45.5008      | 21.8513      | 37.7516      | 41.9987         | 22.7335       | 9     |


### Framework versions

- Transformers 4.27.4
- TensorFlow 2.11.0
- Datasets 2.11.0
- Tokenizers 0.13.3

{"license": "apache-2.0", "tags": ["generated_from_keras_callback"], "model-index": [{"name": "leonardo-simao/t5-small-finetuned-samsum", "results": []}]}
transformers tf tensorboard t5 text2text-generation generated_from_keras_callback license:apache-2.0 autotrain_compatible endpoints_compatible has_space text-generation-inference region:us
TAGS
#transformers #tf #tensorboard #t5 #text2text-generation #generated_from_keras_callback #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #text-generation-inference #region-us 

leonardo-simao/t5-small-finetuned-samsum
========================================


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


* Train Loss: 1.7827
* Validation Loss: 1.6911
* Train Rouge1: 45.5008
* Train Rouge2: 21.8513
* Train Rougel: 37.7516
* Train Rougelsum: 41.9987
* Train Gen Len: 22.7335
* Epoch: 9


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:


* optimizer: {'name': 'AdamWeightDecay', 'learning\_rate': 2e-05, 'decay': 0.0, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight\_decay\_rate': 0.01}
* training\_precision: float32


### Training results



### Framework versions


* Transformers 4.27.4
* TensorFlow 2.11.0
* Datasets 2.11.0
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* optimizer: {'name': 'AdamWeightDecay', 'learning\_rate': 2e-05, 'decay': 0.0, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight\_decay\_rate': 0.01}
* training\_precision: float32 ### Training results ### Framework versions


* Transformers 4.27.4
* TensorFlow 2.11.0
* Datasets 2.11.0
* Tokenizers 0.13.3
TAGS
#transformers #tf #tensorboard #t5 #text2text-generation #generated_from_keras_callback #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #text-generation-inference #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* optimizer: {'name': 'AdamWeightDecay', 'learning\_rate': 2e-05, 'decay': 0.0, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight\_decay\_rate': 0.01}
* training\_precision: float32 ### Training results ### Framework versions


* Transformers 4.27.4
* TensorFlow 2.11.0
* Datasets 2.11.0
* Tokenizers 0.13.3
TAGS
#transformers #tf #tensorboard #t5 #text2text-generation #generated_from_keras_callback #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #text-generation-inference #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* optimizer: {'name': 'AdamWeightDecay', 'learning\_rate': 2e-05, 'decay': 0.0, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight\_decay\_rate': 0.01}
* training\_precision: float32### Training results### Framework versions


* Transformers 4.27.4
* TensorFlow 2.11.0
* Datasets 2.11.0
* Tokenizers 0.13.3