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# cewinharhar/iceCream

This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 1.1909
- Validation Loss: 3.0925
- Epoch: 92

## 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': 2e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01}
- training_precision: float32

### Training results

| Train Loss | Validation Loss | Epoch |
|:----------:|:---------------:|:-----:|
| 4.9926     | 4.0419          | 0     |
| 3.9831     | 3.8247          | 1     |
| 3.8396     | 3.7337          | 2     |
| 3.7352     | 3.6509          | 3     |
| 3.6382     | 3.5948          | 4     |
| 3.5595     | 3.5458          | 5     |
| 3.4845     | 3.4667          | 6     |
| 3.4140     | 3.4460          | 7     |
| 3.3546     | 3.4035          | 8     |
| 3.2939     | 3.3571          | 9     |
| 3.2420     | 3.3465          | 10    |
| 3.1867     | 3.2970          | 11    |
| 3.1418     | 3.2716          | 12    |
| 3.0865     | 3.2609          | 13    |
| 3.0419     | 3.2318          | 14    |
| 2.9962     | 3.2279          | 15    |
| 2.9551     | 3.1991          | 16    |
| 2.9178     | 3.1656          | 17    |
| 2.8701     | 3.1654          | 18    |
| 2.8348     | 3.1372          | 19    |
| 2.7988     | 3.1281          | 20    |
| 2.7597     | 3.0978          | 21    |
| 2.7216     | 3.1019          | 22    |
| 2.6844     | 3.0388          | 23    |
| 2.6489     | 3.0791          | 24    |
| 2.6192     | 3.0885          | 25    |
| 2.5677     | 3.0388          | 26    |
| 2.5478     | 3.0530          | 27    |
| 2.5136     | 3.0403          | 28    |
| 2.4756     | 3.0521          | 29    |
| 2.4454     | 3.0173          | 30    |
| 2.4203     | 3.0079          | 31    |
| 2.3882     | 3.0325          | 32    |
| 2.3596     | 3.0066          | 33    |
| 2.3279     | 2.9919          | 34    |
| 2.2947     | 2.9871          | 35    |
| 2.2712     | 2.9834          | 36    |
| 2.2311     | 2.9917          | 37    |
| 2.2022     | 2.9796          | 38    |
| 2.1703     | 2.9641          | 39    |
| 2.1394     | 2.9571          | 40    |
| 2.1237     | 2.9662          | 41    |
| 2.0949     | 2.9358          | 42    |
| 2.0673     | 2.9653          | 43    |
| 2.0417     | 2.9416          | 44    |
| 2.0194     | 2.9531          | 45    |
| 2.0009     | 2.9417          | 46    |
| 1.9716     | 2.9325          | 47    |
| 1.9488     | 2.9476          | 48    |
| 1.9265     | 2.9559          | 49    |
| 1.8975     | 2.9477          | 50    |
| 1.8815     | 2.9429          | 51    |
| 1.8552     | 2.9119          | 52    |
| 1.8358     | 2.9377          | 53    |
| 1.8226     | 2.9605          | 54    |
| 1.7976     | 2.9446          | 55    |
| 1.7677     | 2.9162          | 56    |
| 1.7538     | 2.9292          | 57    |
| 1.7376     | 2.9968          | 58    |
| 1.7156     | 2.9525          | 59    |
| 1.7001     | 2.9275          | 60    |
| 1.6806     | 2.9714          | 61    |
| 1.6582     | 2.9903          | 62    |
| 1.6436     | 2.9363          | 63    |
| 1.6254     | 2.9714          | 64    |
| 1.6093     | 2.9804          | 65    |
| 1.5900     | 2.9740          | 66    |
| 1.5686     | 2.9835          | 67    |
| 1.5492     | 3.0018          | 68    |
| 1.5371     | 3.0088          | 69    |
| 1.5245     | 2.9780          | 70    |
| 1.5021     | 3.0176          | 71    |
| 1.4839     | 2.9917          | 72    |
| 1.4726     | 3.0602          | 73    |
| 1.4568     | 3.0055          | 74    |
| 1.4435     | 3.0186          | 75    |
| 1.4225     | 2.9948          | 76    |
| 1.4088     | 3.0270          | 77    |
| 1.3947     | 3.0676          | 78    |
| 1.3780     | 3.0615          | 79    |
| 1.3627     | 3.0780          | 80    |
| 1.3445     | 3.0491          | 81    |
| 1.3293     | 3.0534          | 82    |
| 1.3130     | 3.0460          | 83    |
| 1.2980     | 3.0846          | 84    |
| 1.2895     | 3.0709          | 85    |
| 1.2737     | 3.0903          | 86    |
| 1.2557     | 3.0854          | 87    |
| 1.2499     | 3.1101          | 88    |
| 1.2353     | 3.1181          | 89    |
| 1.2104     | 3.1111          | 90    |
| 1.2101     | 3.1153          | 91    |
| 1.1909     | 3.0925          | 92    |


### Framework versions

- Transformers 4.19.2
- TensorFlow 2.9.1
- Datasets 2.1.0
- Tokenizers 0.12.1

{"license": "apache-2.0", "tags": ["generated_from_keras_callback"], "model-index": [{"name": "cewinharhar/iceCream", "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 

cewinharhar/iceCream
====================


This model is a fine-tuned version of t5-base on an unknown dataset.
It achieves the following results on the evaluation set:


* Train Loss: 1.1909
* Validation Loss: 3.0925
* Epoch: 92


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': 2e-05, 'decay': 0.0, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight\_decay\_rate': 0.01}
* training\_precision: float32


### Training results



### Framework versions


* Transformers 4.19.2
* TensorFlow 2.9.1
* Datasets 2.1.0
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* optimizer: {'name': 'AdamWeightDecay', 'learning\_rate': 2e-05, 'decay': 0.0, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight\_decay\_rate': 0.01}
* training\_precision: float32 ### Training results ### Framework versions


* Transformers 4.19.2
* TensorFlow 2.9.1
* Datasets 2.1.0
* Tokenizers 0.12.1
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': 2e-05, 'decay': 0.0, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight\_decay\_rate': 0.01}
* training\_precision: float32 ### Training results ### Framework versions


* Transformers 4.19.2
* TensorFlow 2.9.1
* Datasets 2.1.0
* Tokenizers 0.12.1
passage: 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': 2e-05, 'decay': 0.0, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight\_decay\_rate': 0.01}
* training\_precision: float32### Training results### Framework versions


* Transformers 4.19.2
* TensorFlow 2.9.1
* Datasets 2.1.0
* Tokenizers 0.12.1