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# LucaReggiani/t5-small-nlpfinalprojectFinal_2-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: 3.1437
- Validation Loss: 3.0238
- Train Rouge1: 0.2336
- Train Rouge2: 0.0519
- Train Rougel: 0.1789
- Train Rougelsum: 0.1789
- Train Gen Len: 18.45
- Epoch: 7

## 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': 3e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.1}
- training_precision: float32

### Training results

| Train Loss | Validation Loss | Train Rouge1 | Train Rouge2 | Train Rougel | Train Rougelsum | Train Gen Len | Epoch |
|:----------:|:---------------:|:------------:|:------------:|:------------:|:---------------:|:-------------:|:-----:|
| 3.8777     | 3.3196          | 0.2048       | 0.0442       | 0.1547       | 0.1560          | 18.75         | 0     |
| 3.5167     | 3.1758          | 0.2102       | 0.0457       | 0.1670       | 0.1676          | 18.24         | 1     |
| 3.3968     | 3.1202          | 0.2077       | 0.0439       | 0.1680       | 0.1681          | 18.11         | 2     |
| 3.3297     | 3.0883          | 0.2135       | 0.0444       | 0.1710       | 0.1710          | 18.52         | 3     |
| 3.2789     | 3.0664          | 0.2274       | 0.0500       | 0.1792       | 0.1788          | 18.44         | 4     |
| 3.2279     | 3.0473          | 0.2283       | 0.0510       | 0.1786       | 0.1787          | 18.34         | 5     |
| 3.1857     | 3.0342          | 0.2327       | 0.0534       | 0.1816       | 0.1817          | 18.42         | 6     |
| 3.1437     | 3.0238          | 0.2336       | 0.0519       | 0.1789       | 0.1789          | 18.45         | 7     |


### Framework versions

- Transformers 4.26.1
- TensorFlow 2.11.0
- Datasets 2.10.1
- Tokenizers 0.13.2

{"license": "apache-2.0", "tags": ["generated_from_keras_callback"], "model-index": [{"name": "LucaReggiani/t5-small-nlpfinalprojectFinal_2-xsum", "results": []}]}
transformers tf t5 text2text-generation generated_from_keras_callback license:apache-2.0 autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #tf #t5 #text2text-generation #generated_from_keras_callback #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

LucaReggiani/t5-small-nlpfinalprojectFinal\_2-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: 3.1437
* Validation Loss: 3.0238
* Train Rouge1: 0.2336
* Train Rouge2: 0.0519
* Train Rougel: 0.1789
* Train Rougelsum: 0.1789
* Train Gen Len: 18.45
* Epoch: 7


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': 3e-05, 'decay': 0.0, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight\_decay\_rate': 0.1}
* training\_precision: float32


### Training results



### Framework versions


* Transformers 4.26.1
* TensorFlow 2.11.0
* Datasets 2.10.1
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* optimizer: {'name': 'AdamWeightDecay', 'learning\_rate': 3e-05, 'decay': 0.0, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight\_decay\_rate': 0.1}
* training\_precision: float32 ### Training results ### Framework versions


* Transformers 4.26.1
* TensorFlow 2.11.0
* Datasets 2.10.1
* Tokenizers 0.13.2
TAGS
#transformers #tf #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': 3e-05, 'decay': 0.0, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight\_decay\_rate': 0.1}
* training\_precision: float32 ### Training results ### Framework versions


* Transformers 4.26.1
* TensorFlow 2.11.0
* Datasets 2.10.1
* Tokenizers 0.13.2
TAGS
#transformers #tf #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': 3e-05, 'decay': 0.0, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight\_decay\_rate': 0.1}
* training\_precision: float32### Training results### Framework versions


* Transformers 4.26.1
* TensorFlow 2.11.0
* Datasets 2.10.1
* Tokenizers 0.13.2