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# Prgrg/ja-en-JESC-v4.0-wth-lr-decay

This model is a fine-tuned version of [Prgrg/ja-en-JESC-v3.0-wth-lr-decay](https://huggingface.co/Prgrg/ja-en-JESC-v3.0-wth-lr-decay) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 2.0999
- Validation Loss: 2.5673
- Epoch: 7

## 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': 0.0002, 'decay_schedule_fn': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 0.0002, 'decay_steps': 199000, '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': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.001}
- training_precision: mixed_float16

### Training results

| Train Loss | Validation Loss | Epoch |
|:----------:|:---------------:|:-----:|
| 2.4825     | 2.6526          | 0     |
| 2.4354     | 2.6193          | 1     |
| 2.3724     | 2.5918          | 2     |
| 2.3112     | 2.5749          | 3     |
| 2.2521     | 2.5652          | 4     |
| 2.1967     | 2.5622          | 5     |
| 2.1449     | 2.5608          | 6     |
| 2.0999     | 2.5673          | 7     |


### Framework versions

- Transformers 4.26.1
- TensorFlow 2.11.0
- Datasets 2.10.1
- Tokenizers 0.13.2

{"license": "apache-2.0", "tags": ["generated_from_keras_callback"], "model-index": [{"name": "Prgrg/ja-en-JESC-v4.0-wth-lr-decay", "results": []}]}
transformers tf marian text2text-generation generated_from_keras_callback license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #tf #marian #text2text-generation #generated_from_keras_callback #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 

Prgrg/ja-en-JESC-v4.0-wth-lr-decay
==================================


This model is a fine-tuned version of Prgrg/ja-en-JESC-v3.0-wth-lr-decay on an unknown dataset.
It achieves the following results on the evaluation set:


* Train Loss: 2.0999
* Validation Loss: 2.5673
* Epoch: 7


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': 0.0002, 'decay\_schedule\_fn': {'class\_name': 'PolynomialDecay', 'config': {'initial\_learning\_rate': 0.0002, 'decay\_steps': 199000, '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': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight\_decay\_rate': 0.001}
* training\_precision: mixed\_float16


### Training results



### Framework versions


* Transformers 4.26.1
* TensorFlow 2.11.0
* Datasets 2.10.1
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* optimizer: {'name': 'AdamWeightDecay', 'learning\_rate': {'class\_name': 'WarmUp', 'config': {'initial\_learning\_rate': 0.0002, 'decay\_schedule\_fn': {'class\_name': 'PolynomialDecay', 'config': {'initial\_learning\_rate': 0.0002, 'decay\_steps': 199000, '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': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight\_decay\_rate': 0.001}
* training\_precision: mixed\_float16 ### Training results ### Framework versions


* Transformers 4.26.1
* TensorFlow 2.11.0
* Datasets 2.10.1
* Tokenizers 0.13.2
TAGS
#transformers #tf #marian #text2text-generation #generated_from_keras_callback #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* optimizer: {'name': 'AdamWeightDecay', 'learning\_rate': {'class\_name': 'WarmUp', 'config': {'initial\_learning\_rate': 0.0002, 'decay\_schedule\_fn': {'class\_name': 'PolynomialDecay', 'config': {'initial\_learning\_rate': 0.0002, 'decay\_steps': 199000, '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': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight\_decay\_rate': 0.001}
* training\_precision: mixed\_float16 ### Training results ### Framework versions


* Transformers 4.26.1
* TensorFlow 2.11.0
* Datasets 2.10.1
* Tokenizers 0.13.2
TAGS
#transformers #tf #marian #text2text-generation #generated_from_keras_callback #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* optimizer: {'name': 'AdamWeightDecay', 'learning\_rate': {'class\_name': 'WarmUp', 'config': {'initial\_learning\_rate': 0.0002, 'decay\_schedule\_fn': {'class\_name': 'PolynomialDecay', 'config': {'initial\_learning\_rate': 0.0002, 'decay\_steps': 199000, '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': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight\_decay\_rate': 0.001}
* training\_precision: mixed\_float16### Training results### Framework versions


* Transformers 4.26.1
* TensorFlow 2.11.0
* Datasets 2.10.1
* Tokenizers 0.13.2