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# LucaReggiani/t5-small-nlpfinalproject12_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: 3.8830
- Validation Loss: 3.5699
- Train Rouge1: 18.4656
- Train Rouge2: 2.2126
- Train Rougel: 14.7442
- Train Rougelsum: 15.1761
- Train Gen Len: 18.96
- 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': 'SGD', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': True, 'is_legacy_optimizer': False, 'learning_rate': 1.9e-05, 'momentum': 0.9, 'nesterov': False}
- training_precision: float32

### Training results

| Train Loss | Validation Loss | Train Rouge1 | Train Rouge2 | Train Rougel | Train Rougelsum | Train Gen Len | Epoch |
|:----------:|:---------------:|:------------:|:------------:|:------------:|:---------------:|:-------------:|:-----:|
| 4.3168     | 4.0297          | 15.0947      | 2.1725       | 12.0181      | 11.8872         | 19.0          | 0     |
| 4.1683     | 3.9156          | 16.1828      | 1.9876       | 12.9115      | 13.0799         | 19.0          | 1     |
| 4.0819     | 3.8338          | 15.9429      | 1.9947       | 13.0026      | 13.1274         | 19.0          | 2     |
| 4.0326     | 3.7649          | 16.7647      | 2.5233       | 13.4735      | 13.6475         | 18.96         | 3     |
| 3.9797     | 3.7033          | 17.2322      | 2.6240       | 13.6267      | 13.7851         | 18.95         | 4     |
| 3.9348     | 3.6524          | 17.4618      | 2.0566       | 13.5028      | 13.8150         | 18.98         | 5     |
| 3.8988     | 3.6090          | 17.7496      | 2.1414       | 13.8788      | 14.3797         | 18.98         | 6     |
| 3.8830     | 3.5699          | 18.4656      | 2.2126       | 14.7442      | 15.1761         | 18.96         | 7     |


### Framework versions

- Transformers 4.26.1
- TensorFlow 2.11.0
- Datasets 2.10.0
- Tokenizers 0.13.2

{"license": "apache-2.0", "tags": ["generated_from_keras_callback"], "model-index": [{"name": "LucaReggiani/t5-small-nlpfinalproject12_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-nlpfinalproject12\_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: 3.8830
* Validation Loss: 3.5699
* Train Rouge1: 18.4656
* Train Rouge2: 2.2126
* Train Rougel: 14.7442
* Train Rougelsum: 15.1761
* Train Gen Len: 18.96
* 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': 'SGD', 'weight\_decay': None, 'clipnorm': None, 'global\_clipnorm': None, 'clipvalue': None, 'use\_ema': False, 'ema\_momentum': 0.99, 'ema\_overwrite\_frequency': None, 'jit\_compile': True, 'is\_legacy\_optimizer': False, 'learning\_rate': 1.9e-05, 'momentum': 0.9, 'nesterov': False}
* training\_precision: float32


### Training results



### Framework versions


* Transformers 4.26.1
* TensorFlow 2.11.0
* Datasets 2.10.0
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* optimizer: {'name': 'SGD', 'weight\_decay': None, 'clipnorm': None, 'global\_clipnorm': None, 'clipvalue': None, 'use\_ema': False, 'ema\_momentum': 0.99, 'ema\_overwrite\_frequency': None, 'jit\_compile': True, 'is\_legacy\_optimizer': False, 'learning\_rate': 1.9e-05, 'momentum': 0.9, 'nesterov': False}
* training\_precision: float32 ### Training results ### Framework versions


* Transformers 4.26.1
* TensorFlow 2.11.0
* Datasets 2.10.0
* 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': 'SGD', 'weight\_decay': None, 'clipnorm': None, 'global\_clipnorm': None, 'clipvalue': None, 'use\_ema': False, 'ema\_momentum': 0.99, 'ema\_overwrite\_frequency': None, 'jit\_compile': True, 'is\_legacy\_optimizer': False, 'learning\_rate': 1.9e-05, 'momentum': 0.9, 'nesterov': False}
* training\_precision: float32 ### Training results ### Framework versions


* Transformers 4.26.1
* TensorFlow 2.11.0
* Datasets 2.10.0
* 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': 'SGD', 'weight\_decay': None, 'clipnorm': None, 'global\_clipnorm': None, 'clipvalue': None, 'use\_ema': False, 'ema\_momentum': 0.99, 'ema\_overwrite\_frequency': None, 'jit\_compile': True, 'is\_legacy\_optimizer': False, 'learning\_rate': 1.9e-05, 'momentum': 0.9, 'nesterov': False}
* training\_precision: float32### Training results### Framework versions


* Transformers 4.26.1
* TensorFlow 2.11.0
* Datasets 2.10.0
* Tokenizers 0.13.2