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

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: 2.3942
- Validation Loss: 2.2286
- Train Rouge1: 33.3833
- Train Rouge2: 10.8793
- Train Rougel: 26.0564
- Train Rougelsum: 26.0512
- Train Gen Len: 27.1770
- 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 |
|:----------:|:---------------:|:------------:|:------------:|:------------:|:---------------:|:-------------:|:-----:|
| 2.7789     | 2.4538          | 30.3134      | 8.5372       | 23.4244      | 23.4213         | 26.4852       | 0     |
| 2.6453     | 2.3911          | 31.1672      | 9.2021       | 24.1447      | 24.1417         | 26.7193       | 1     |
| 2.5853     | 2.3522          | 31.6995      | 9.5664       | 24.5990      | 24.5978         | 26.7451       | 2     |
| 2.5415     | 2.3241          | 32.1058      | 9.8659       | 24.9344      | 24.9268         | 27.0580       | 3     |
| 2.5079     | 2.3014          | 32.2524      | 9.9560       | 25.0746      | 25.0706         | 26.9969       | 4     |
| 2.4789     | 2.2830          | 32.4974      | 10.1997      | 25.2473      | 25.2441         | 27.0349       | 5     |
| 2.4532     | 2.2672          | 32.7655      | 10.3607      | 25.4207      | 25.4145         | 27.0304       | 6     |
| 2.4324     | 2.2546          | 33.0104      | 10.6010      | 25.6580      | 25.6574         | 27.0998       | 7     |
| 2.4126     | 2.2416          | 33.3930      | 10.8337      | 26.0110      | 26.0049         | 27.1842       | 8     |
| 2.3942     | 2.2286          | 33.3833      | 10.8793      | 26.0564      | 26.0512         | 27.1770       | 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-xsum", "results": []}]}
transformers tf tensorboard t5 text2text-generation generated_from_keras_callback license:apache-2.0 autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #tf #tensorboard #t5 #text2text-generation #generated_from_keras_callback #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

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


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: 2.3942
* Validation Loss: 2.2286
* Train Rouge1: 33.3833
* Train Rouge2: 10.8793
* Train Rougel: 26.0564
* Train Rougelsum: 26.0512
* Train Gen Len: 27.1770
* 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 #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 #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