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# t5_8_3e-5_datav2_min30_lp2_sample

This model is a fine-tuned version of [KETI-AIR/ke-t5-large-ko](https://huggingface.co/KETI-AIR/ke-t5-large-ko) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 6.2375
- Rouge1: 24.1102
- Rouge2: 5.3137
- Rougel: 16.1086
- Bleu1: 18.6424
- Bleu2: 8.0483
- Bleu3: 2.7046
- Bleu4: 0.7308
- Gen Len: 36.4012

## 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:
- learning_rate: 3e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10.0

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge1  | Rouge2 | Rougel  | Bleu1   | Bleu2  | Bleu3  | Bleu4  | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:------:|:-------:|:-------:|:------:|:------:|:------:|:-------:|
| 4.1641        | 1.04  | 5000  | 6.8094          | 21.6187 | 4.959  | 14.8344 | 16.9553 | 7.4791 | 2.8017 | 1.1852 | 38.0426 |
| 3.1804        | 2.08  | 10000 | 5.6664          | 22.2631 | 5.127  | 15.5533 | 16.881  | 7.515  | 2.8628 | 1.0614 | 33.7325 |
| 2.779         | 3.12  | 15000 | 5.3350          | 22.5781 | 5.1137 | 15.7717 | 16.8632 | 7.3067 | 2.7117 | 0.9906 | 31.459  |
| 2.4111        | 4.15  | 20000 | 5.2687          | 24.4915 | 6.003  | 16.8096 | 18.5998 | 8.54   | 3.4084 | 1.1511 | 32.7477 |
| 2.2192        | 5.19  | 25000 | 5.3300          | 24.9661 | 6.0773 | 16.8486 | 19.0105 | 8.6794 | 3.4052 | 1.3281 | 32.9696 |
| 1.9306        | 6.23  | 30000 | 5.4806          | 24.8662 | 5.9711 | 16.235  | 19.2093 | 8.7044 | 3.2412 | 1.0675 | 35.0973 |
| 1.6696        | 7.27  | 35000 | 5.6865          | 24.3913 | 5.6936 | 16.4663 | 18.5884 | 8.3035 | 2.9593 | 1.0997 | 34.617  |
| 1.4566        | 8.31  | 40000 | 5.8677          | 24.9166 | 5.8251 | 16.647  | 19.0703 | 8.5159 | 3.3477 | 1.1257 | 35.1763 |
| 1.2808        | 9.35  | 45000 | 6.2375          | 24.1102 | 5.3137 | 16.1086 | 18.6424 | 8.0483 | 2.7046 | 0.7308 | 36.4012 |


### Framework versions

- Transformers 4.25.1
- Pytorch 1.13.0+cu117
- Datasets 2.7.1
- Tokenizers 0.13.2

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["rouge"], "model-index": [{"name": "t5_8_3e-5_datav2_min30_lp2_sample", "results": []}]}
transformers pytorch tensorboard t5 text2text-generation generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #tensorboard #t5 #text2text-generation #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

t5\_8\_3e-5\_datav2\_min30\_lp2\_sample
=======================================


This model is a fine-tuned version of KETI-AIR/ke-t5-large-ko on an unknown dataset.
It achieves the following results on the evaluation set:


* Loss: 6.2375
* Rouge1: 24.1102
* Rouge2: 5.3137
* Rougel: 16.1086
* Bleu1: 18.6424
* Bleu2: 8.0483
* Bleu3: 2.7046
* Bleu4: 0.7308
* Gen Len: 36.4012


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:


* learning\_rate: 3e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.1
* num\_epochs: 10.0


### Training results



### Framework versions


* Transformers 4.25.1
* Pytorch 1.13.0+cu117
* Datasets 2.7.1
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 3e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.1
* num\_epochs: 10.0 ### Training results ### Framework versions


* Transformers 4.25.1
* Pytorch 1.13.0+cu117
* Datasets 2.7.1
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #t5 #text2text-generation #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 3e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.1
* num\_epochs: 10.0 ### Training results ### Framework versions


* Transformers 4.25.1
* Pytorch 1.13.0+cu117
* Datasets 2.7.1
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #t5 #text2text-generation #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 3e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.1
* num\_epochs: 10.0### Training results### Framework versions


* Transformers 4.25.1
* Pytorch 1.13.0+cu117
* Datasets 2.7.1
* Tokenizers 0.13.2