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# madatnlp/mt5-kormath

This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.7119
- Validation Loss: 1.1299
- Epoch: 61

## 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': 0.001, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
- training_precision: mixed_bfloat16

### Training results

| Train Loss | Validation Loss | Epoch |
|:----------:|:---------------:|:-----:|
| 17.9929    | 5.9287          | 0     |
| 5.4802     | 3.9942          | 1     |
| 4.1718     | 3.2517          | 2     |
| 3.5750     | 2.9586          | 3     |
| 3.1535     | 2.4970          | 4     |
| 2.8665     | 2.4626          | 5     |
| 2.6682     | 2.3795          | 6     |
| 2.5323     | 2.2238          | 7     |
| 2.4057     | 2.0684          | 8     |
| 2.3107     | 2.2033          | 9     |
| 2.2501     | 1.8339          | 10    |
| 2.1089     | 1.9064          | 11    |
| 2.0741     | 2.0256          | 12    |
| 1.9868     | 1.8107          | 13    |
| 1.9719     | 1.7157          | 14    |
| 1.8762     | 1.6966          | 15    |
| 1.8814     | 1.6580          | 16    |
| 1.8052     | 1.6043          | 17    |
| 1.7567     | 1.6572          | 18    |
| 1.7209     | 1.5485          | 19    |
| 1.7347     | 1.6464          | 20    |
| 1.6760     | 1.5892          | 21    |
| 1.6286     | 1.5765          | 22    |
| 1.6124     | 1.7408          | 23    |
| 1.5683     | 1.4875          | 24    |
| 1.5814     | 1.4448          | 25    |
| 1.5306     | 1.4902          | 26    |
| 1.5121     | 1.5133          | 27    |
| 1.4869     | 1.4217          | 28    |
| 1.4539     | 1.5602          | 29    |
| 1.4650     | 1.4699          | 30    |
| 1.4508     | 1.4319          | 31    |
| 1.3910     | 1.5975          | 32    |
| 1.3758     | 1.4031          | 33    |
| 1.3550     | 1.4295          | 34    |
| 1.3405     | 1.3804          | 35    |
| 1.3144     | 1.4202          | 36    |
| 1.3136     | 1.5135          | 37    |
| 1.2617     | 1.4790          | 38    |
| 1.2260     | 1.4108          | 39    |
| 1.2348     | 1.3108          | 40    |
| 1.2019     | 1.1461          | 41    |
| 1.1775     | 1.2509          | 42    |
| 1.1690     | 1.2179          | 43    |
| 1.1318     | 1.2483          | 44    |
| 1.1013     | 1.0815          | 45    |
| 1.0735     | 1.2135          | 46    |
| 1.0439     | 1.1260          | 47    |
| 1.0182     | 1.1993          | 48    |
| 0.9971     | 1.0797          | 49    |
| 0.9583     | 1.2587          | 50    |
| 0.9505     | 1.0793          | 51    |
| 0.9366     | 1.0501          | 52    |
| 0.9170     | 1.1476          | 53    |
| 0.8741     | 1.0560          | 54    |
| 0.8558     | 1.0024          | 55    |
| 0.8394     | 0.9604          | 56    |
| 0.8203     | 1.2700          | 57    |
| 0.7938     | 1.1081          | 58    |
| 0.7800     | 1.0198          | 59    |
| 0.7378     | 1.1748          | 60    |
| 0.7119     | 1.1299          | 61    |


### Framework versions

- Transformers 4.18.0
- TensorFlow 2.8.0
- Datasets 2.2.0
- Tokenizers 0.12.1

{"license": "apache-2.0", "tags": ["generated_from_keras_callback"], "model-index": [{"name": "madatnlp/mt5-kormath", "results": []}]}
transformers tf mt5 text2text-generation generated_from_keras_callback license:apache-2.0 autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #tf #mt5 #text2text-generation #generated_from_keras_callback #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

madatnlp/mt5-kormath
====================


This model is a fine-tuned version of google/mt5-small on an unknown dataset.
It achieves the following results on the evaluation set:


* Train Loss: 0.7119
* Validation Loss: 1.1299
* Epoch: 61


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': 0.001, 'decay': 0.0, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
* training\_precision: mixed\_bfloat16


### Training results



### Framework versions


* Transformers 4.18.0
* TensorFlow 2.8.0
* Datasets 2.2.0
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* optimizer: {'name': 'Adam', 'learning\_rate': 0.001, 'decay': 0.0, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
* training\_precision: mixed\_bfloat16 ### Training results ### Framework versions


* Transformers 4.18.0
* TensorFlow 2.8.0
* Datasets 2.2.0
* Tokenizers 0.12.1
TAGS
#transformers #tf #mt5 #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', 'learning\_rate': 0.001, 'decay': 0.0, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
* training\_precision: mixed\_bfloat16 ### Training results ### Framework versions


* Transformers 4.18.0
* TensorFlow 2.8.0
* Datasets 2.2.0
* Tokenizers 0.12.1
passage: TAGS
#transformers #tf #mt5 #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', 'learning\_rate': 0.001, 'decay': 0.0, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
* training\_precision: mixed\_bfloat16### Training results### Framework versions


* Transformers 4.18.0
* TensorFlow 2.8.0
* Datasets 2.2.0
* Tokenizers 0.12.1