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# gpt_image_clef2

This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 1.2611
- Train Rouge: 0.4475
- Validation Loss: 1.1578
- Validation Rouge: 0.3944
- Epoch: 25

## 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': {'class_name': 'WarmUp', 'config': {'initial_learning_rate': 0.0005, 'decay_schedule_fn': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 0.0005, 'decay_steps': 2554800, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, '__passive_serialization__': True}, 'warmup_steps': 1000, 'power': 1.0, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.99, 'epsilon': 0.2, 'amsgrad': False, 'weight_decay_rate': 0.01}
- training_precision: float32

### Training results

| Train Loss | Train Rouge | Validation Loss | Validation Rouge | Epoch |
|:----------:|:-----------:|:---------------:|:----------------:|:-----:|
| 1.5255     | 0.4213      | 1.0251          | 0.4284           | 0     |
| 1.1805     | 0.4673      | 0.9779          | 0.4442           | 1     |
| 1.1394     | 0.4800      | 0.9561          | 0.4509           | 2     |
| 1.1168     | 0.4871      | 0.9369          | 0.4595           | 3     |
| 1.1036     | 0.4915      | 0.9314          | 0.4623           | 4     |
| 1.0971     | 0.4936      | 0.9283          | 0.4624           | 5     |
| 1.0946     | 0.4947      | 0.9315          | 0.4617           | 6     |
| 1.0962     | 0.4947      | 0.9323          | 0.4614           | 7     |
| 1.1001     | 0.4943      | 0.9405          | 0.4586           | 8     |
| 1.1065     | 0.4933      | 0.9501          | 0.4560           | 9     |
| 1.1146     | 0.4913      | 0.9614          | 0.4498           | 10    |
| 1.1240     | 0.4890      | 0.9726          | 0.4471           | 11    |
| 1.1341     | 0.4864      | 0.9852          | 0.4429           | 12    |
| 1.1451     | 0.4836      | 0.9982          | 0.4389           | 13    |
| 1.1564     | 0.4799      | 1.0160          | 0.4319           | 14    |
| 1.1680     | 0.4766      | 1.0273          | 0.4296           | 15    |
| 1.1793     | 0.4732      | 1.0405          | 0.4267           | 16    |
| 1.1901     | 0.4699      | 1.0556          | 0.4235           | 17    |
| 1.2007     | 0.4666      | 1.0692          | 0.4184           | 18    |
| 1.2108     | 0.4632      | 1.0796          | 0.4168           | 19    |
| 1.2207     | 0.4603      | 1.0998          | 0.4093           | 20    |
| 1.2299     | 0.4574      | 1.1135          | 0.4057           | 21    |
| 1.2386     | 0.4547      | 1.1297          | 0.4026           | 22    |
| 1.2469     | 0.4519      | 1.1396          | 0.4013           | 23    |
| 1.2540     | 0.4497      | 1.1467          | 0.3960           | 24    |
| 1.2611     | 0.4475      | 1.1578          | 0.3944           | 25    |


### Framework versions

- Transformers 4.28.1
- TensorFlow 2.10.1
- Datasets 2.11.0
- Tokenizers 0.13.3

{"license": "mit", "tags": ["generated_from_keras_callback"], "model-index": [{"name": "gpt_image_clef2", "results": []}]}
transformers tf gpt2 text-generation generated_from_keras_callback license:mit autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #tf #gpt2 #text-generation #generated_from_keras_callback #license-mit #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

gpt\_image\_clef2
=================


This model is a fine-tuned version of gpt2 on an unknown dataset.
It achieves the following results on the evaluation set:


* Train Loss: 1.2611
* Train Rouge: 0.4475
* Validation Loss: 1.1578
* Validation Rouge: 0.3944
* Epoch: 25


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': {'class\_name': 'WarmUp', 'config': {'initial\_learning\_rate': 0.0005, 'decay\_schedule\_fn': {'class\_name': 'PolynomialDecay', 'config': {'initial\_learning\_rate': 0.0005, 'decay\_steps': 2554800, 'end\_learning\_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, '**passive\_serialization**': True}, 'warmup\_steps': 1000, 'power': 1.0, 'name': None}}, 'decay': 0.0, 'beta\_1': 0.9, 'beta\_2': 0.99, 'epsilon': 0.2, 'amsgrad': False, 'weight\_decay\_rate': 0.01}
* training\_precision: float32


### Training results



### Framework versions


* Transformers 4.28.1
* TensorFlow 2.10.1
* Datasets 2.11.0
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* optimizer: {'name': 'AdamWeightDecay', 'learning\_rate': {'class\_name': 'WarmUp', 'config': {'initial\_learning\_rate': 0.0005, 'decay\_schedule\_fn': {'class\_name': 'PolynomialDecay', 'config': {'initial\_learning\_rate': 0.0005, 'decay\_steps': 2554800, 'end\_learning\_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, '**passive\_serialization**': True}, 'warmup\_steps': 1000, 'power': 1.0, 'name': None}}, 'decay': 0.0, 'beta\_1': 0.9, 'beta\_2': 0.99, 'epsilon': 0.2, 'amsgrad': False, 'weight\_decay\_rate': 0.01}
* training\_precision: float32 ### Training results ### Framework versions


* Transformers 4.28.1
* TensorFlow 2.10.1
* Datasets 2.11.0
* Tokenizers 0.13.3
TAGS
#transformers #tf #gpt2 #text-generation #generated_from_keras_callback #license-mit #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* optimizer: {'name': 'AdamWeightDecay', 'learning\_rate': {'class\_name': 'WarmUp', 'config': {'initial\_learning\_rate': 0.0005, 'decay\_schedule\_fn': {'class\_name': 'PolynomialDecay', 'config': {'initial\_learning\_rate': 0.0005, 'decay\_steps': 2554800, 'end\_learning\_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, '**passive\_serialization**': True}, 'warmup\_steps': 1000, 'power': 1.0, 'name': None}}, 'decay': 0.0, 'beta\_1': 0.9, 'beta\_2': 0.99, 'epsilon': 0.2, 'amsgrad': False, 'weight\_decay\_rate': 0.01}
* training\_precision: float32 ### Training results ### Framework versions


* Transformers 4.28.1
* TensorFlow 2.10.1
* Datasets 2.11.0
* Tokenizers 0.13.3