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# madatnlp/ke-t5-scratch

This model is a fine-tuned version of [madatnlp/ke-t5-math-py](https://huggingface.co/madatnlp/ke-t5-math-py) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.4760
- Validation Loss: 0.7360
- Epoch: 36

## 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', 'learning_rate': 1e-04, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
- training_precision: float32

### Training results

| Train Loss | Validation Loss | Epoch |
|:----------:|:---------------:|:-----:|
| 4.2751     | 2.1074          | 0     |
| 2.2716     | 1.7945          | 1     |
| 1.8889     | 1.5726          | 2     |
| 1.6760     | 1.3722          | 3     |
| 1.5021     | 1.3280          | 4     |
| 1.4369     | 1.2523          | 5     |
| 1.3352     | 1.0619          | 6     |
| 1.2749     | 1.1156          | 7     |
| 1.2170     | 1.0452          | 8     |
| 1.1713     | 1.0596          | 9     |
| 1.1410     | 1.0080          | 10    |
| 1.0884     | 1.0213          | 11    |
| 1.0508     | 0.9223          | 12    |
| 0.9933     | 0.9353          | 13    |
| 0.9871     | 0.8749          | 14    |
| 0.9251     | 0.9173          | 15    |
| 0.9282     | 0.8620          | 16    |
| 0.8849     | 0.8093          | 17    |
| 0.8613     | 0.7823          | 18    |
| 0.8322     | 0.8016          | 19    |
| 0.8070     | 0.8844          | 20    |
| 0.7737     | 0.7635          | 21    |
| 0.7465     | 0.8440          | 22    |
| 0.7178     | 0.7958          | 23    |
| 0.7036     | 0.7739          | 24    |
| 0.6813     | 0.7347          | 25    |
| 0.6597     | 0.7545          | 26    |
| 0.6427     | 0.7394          | 27    |
| 0.6154     | 0.7212          | 28    |
| 0.5892     | 0.7653          | 29    |
| 0.5696     | 0.7073          | 30    |
| 0.5644     | 0.6977          | 31    |
| 0.5307     | 0.6977          | 32    |
| 0.5159     | 0.7736          | 33    |
| 0.5131     | 0.8138          | 34    |
| 0.4812     | 0.7623          | 35    |
| 0.4760     | 0.7360          | 36    |


### Framework versions

- Transformers 4.18.0
- TensorFlow 2.8.0
- Datasets 2.1.0
- Tokenizers 0.12.1

{"tags": ["generated_from_keras_callback"], "model-index": [{"name": "madatnlp/ke-t5-scratch", "results": []}]}
transformers tf t5 text2text-generation generated_from_keras_callback autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #tf #t5 #text2text-generation #generated_from_keras_callback #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

madatnlp/ke-t5-scratch
======================


This model is a fine-tuned version of madatnlp/ke-t5-math-py on an unknown dataset.
It achieves the following results on the evaluation set:


* Train Loss: 0.4760
* Validation Loss: 0.7360
* Epoch: 36


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', 'learning\_rate': 1e-04, 'decay': 0.0, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
* training\_precision: float32


### Training results



### Framework versions


* Transformers 4.18.0
* TensorFlow 2.8.0
* Datasets 2.1.0
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* optimizer: {'name': 'Adam', 'learning\_rate': 1e-04, 'decay': 0.0, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
* training\_precision: float32 ### Training results ### Framework versions


* Transformers 4.18.0
* TensorFlow 2.8.0
* Datasets 2.1.0
* Tokenizers 0.12.1
TAGS
#transformers #tf #t5 #text2text-generation #generated_from_keras_callback #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* optimizer: {'name': 'Adam', 'learning\_rate': 1e-04, 'decay': 0.0, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
* training\_precision: float32 ### Training results ### Framework versions


* Transformers 4.18.0
* TensorFlow 2.8.0
* Datasets 2.1.0
* Tokenizers 0.12.1
passage: TAGS
#transformers #tf #t5 #text2text-generation #generated_from_keras_callback #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* optimizer: {'name': 'Adam', 'learning\_rate': 1e-04, 'decay': 0.0, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
* training\_precision: float32### Training results### Framework versions


* Transformers 4.18.0
* TensorFlow 2.8.0
* Datasets 2.1.0
* Tokenizers 0.12.1