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# LucaReggiani/t5-small-12nlpfinalproject15-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: 3.5850
- Validation Loss: 3.2639
- Train Rouge1: 18.8102
- Train Rouge2: 2.7207
- Train Rougel: 15.0053
- Train Rougelsum: 15.0497
- Train Gen Len: 18.64
- Epoch: 10

## 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': 'Adam', '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': 5e-06, 'beta_1': 0.9, 'beta_2': 0.98, 'epsilon': 1e-06, 'amsgrad': False}
- training_precision: float32

### Training results

| Train Loss | Validation Loss | Train Rouge1 | Train Rouge2 | Train Rougel | Train Rougelsum | Train Gen Len | Epoch |
|:----------:|:---------------:|:------------:|:------------:|:------------:|:---------------:|:-------------:|:-----:|
| 4.2808     | 4.0689          | 16.0766      | 2.2326       | 13.0430      | 13.1934         | 18.94         | 0     |
| 4.1592     | 3.9169          | 16.3671      | 2.1832       | 13.1457      | 13.1612         | 18.94         | 1     |
| 4.0568     | 3.7837          | 16.9390      | 2.4651       | 13.4669      | 13.3983         | 18.94         | 2     |
| 3.9491     | 3.6722          | 17.5351      | 2.5526       | 13.6178      | 13.5941         | 19.0          | 3     |
| 3.8595     | 3.5787          | 17.1791      | 2.2937       | 13.4932      | 13.6093         | 18.93         | 4     |
| 3.7966     | 3.4995          | 17.3785      | 2.5408       | 13.3783      | 13.5736         | 18.98         | 5     |
| 3.7362     | 3.4312          | 18.1473      | 2.7662       | 14.0010      | 14.1828         | 18.99         | 6     |
| 3.6869     | 3.3778          | 17.7556      | 2.6157       | 13.9773      | 13.9192         | 18.8          | 7     |
| 3.6454     | 3.3323          | 18.1910      | 2.3216       | 14.3097      | 14.3738         | 18.76         | 8     |
| 3.5987     | 3.2942          | 18.3254      | 2.5627       | 14.6577      | 14.7984         | 18.73         | 9     |
| 3.5850     | 3.2639          | 18.8102      | 2.7207       | 15.0053      | 15.0497         | 18.64         | 10    |


### 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-12nlpfinalproject15-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-12nlpfinalproject15-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: 3.5850
* Validation Loss: 3.2639
* Train Rouge1: 18.8102
* Train Rouge2: 2.7207
* Train Rougel: 15.0053
* Train Rougelsum: 15.0497
* Train Gen Len: 18.64
* Epoch: 10


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': 'Adam', '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': 5e-06, 'beta\_1': 0.9, 'beta\_2': 0.98, 'epsilon': 1e-06, 'amsgrad': 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': 'Adam', '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': 5e-06, 'beta\_1': 0.9, 'beta\_2': 0.98, 'epsilon': 1e-06, 'amsgrad': 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': 'Adam', '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': 5e-06, 'beta\_1': 0.9, 'beta\_2': 0.98, 'epsilon': 1e-06, 'amsgrad': 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': 'Adam', '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': 5e-06, 'beta\_1': 0.9, 'beta\_2': 0.98, 'epsilon': 1e-06, 'amsgrad': False}
* training\_precision: float32### Training results### Framework versions


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