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# LucaReggiani/t5-small-nlpfinalproject99-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: 3.0379
- Validation Loss: 2.9903
- Train Rouge1: 23.6196
- Train Rouge2: 5.8829
- Train Rougel: 18.9509
- Train Rougelsum: 19.0041
- Train Gen Len: 18.6
- 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': 3e-05, '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 |
|:----------:|:---------------:|:------------:|:------------:|:------------:|:---------------:|:-------------:|:-----:|
| 3.8865     | 3.3185          | 17.9926      | 2.6334       | 14.3776      | 14.4109         | 18.74         | 0     |
| 3.5092     | 3.1756          | 19.9492      | 3.6172       | 15.6914      | 15.7191         | 18.31         | 1     |
| 3.4012     | 3.1160          | 21.2372      | 4.0016       | 16.5756      | 16.5655         | 18.45         | 2     |
| 3.3268     | 3.0809          | 21.5751      | 4.0776       | 16.5050      | 16.5345         | 18.58         | 3     |
| 3.2660     | 3.0550          | 21.7071      | 4.1832       | 16.8604      | 16.8708         | 18.64         | 4     |
| 3.2125     | 3.0377          | 21.9791      | 4.8202       | 17.3234      | 17.3660         | 18.46         | 5     |
| 3.1829     | 3.0218          | 22.4277      | 5.0402       | 17.7633      | 17.8109         | 18.64         | 6     |
| 3.1358     | 3.0142          | 23.5653      | 5.3418       | 18.8989      | 18.9198         | 18.64         | 7     |
| 3.1011     | 3.0042          | 23.1459      | 5.0797       | 18.3238      | 18.3087         | 18.62         | 8     |
| 3.0681     | 2.9995          | 22.9719      | 4.9597       | 17.9675      | 17.9490         | 18.57         | 9     |
| 3.0379     | 2.9903          | 23.6196      | 5.8829       | 18.9509      | 19.0041         | 18.6          | 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-nlpfinalproject99-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-nlpfinalproject99-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: 3.0379
* Validation Loss: 2.9903
* Train Rouge1: 23.6196
* Train Rouge2: 5.8829
* Train Rougel: 18.9509
* Train Rougelsum: 19.0041
* Train Gen Len: 18.6
* 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': 3e-05, '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': 3e-05, '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': 3e-05, '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': 3e-05, '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