
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# flan-t5-large-nlg-multiwoz2.0_400

This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9323
- Rouge1: 36.3522
- Rouge2: 19.5982
- Rougel: 33.0495
- Rougelsum: 34.4791
- Gen Len: 17.7927

## 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: 2e-05
- train_batch_size: 8
- eval_batch_size: 24
- seed: 1799
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 1.4929        | 0.58  | 200  | 1.1051          | 33.8407 | 17.022  | 30.6518 | 32.2374   | 17.7195 |
| 1.1546        | 1.17  | 400  | 1.0221          | 33.4159 | 17.73   | 30.4168 | 31.6796   | 17.8444 |
| 1.0597        | 1.75  | 600  | 0.9819          | 34.8735 | 18.3373 | 31.5435 | 33.0184   | 17.7802 |
| 0.9863        | 2.33  | 800  | 0.9672          | 34.7204 | 18.0945 | 31.5299 | 32.9849   | 17.6341 |
| 0.9689        | 2.92  | 1000 | 0.9509          | 35.7006 | 19.2988 | 32.4312 | 33.8706   | 17.8081 |
| 0.9279        | 3.5   | 1200 | 0.9432          | 35.5086 | 19.1375 | 32.3084 | 33.7471   | 17.9298 |
| 0.9187        | 4.08  | 1400 | 0.9414          | 35.591  | 19.3273 | 32.4831 | 33.914    | 17.7133 |
| 0.8865        | 4.66  | 1600 | 0.9323          | 36.3522 | 19.5982 | 33.0495 | 34.4791   | 17.7927 |
| 0.8735        | 5.25  | 1800 | 0.9311          | 35.7889 | 18.75   | 32.3179 | 33.9012   | 17.8027 |
| 0.8556        | 5.83  | 2000 | 0.9284          | 36.1266 | 19.5539 | 32.7835 | 34.263    | 17.7171 |
| 0.8479        | 6.41  | 2200 | 0.9277          | 36.21   | 19.5396 | 32.8933 | 34.3317   | 17.8339 |


### Framework versions

- Transformers 4.18.0
- Pytorch 1.10.0+cu111
- Datasets 2.5.1
- Tokenizers 0.12.1

{"tags": ["generated_from_trainer"], "metrics": ["rouge"], "model-index": [{"name": "flan-t5-large-nlg-multiwoz2.0_400", "results": []}]}
transformers pytorch t5 text2text-generation generated_from_trainer autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #t5 #text2text-generation #generated_from_trainer #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

flan-t5-large-nlg-multiwoz2.0\_400
==================================


This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 0.9323
* Rouge1: 36.3522
* Rouge2: 19.5982
* Rougel: 33.0495
* Rougelsum: 34.4791
* Gen Len: 17.7927


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: 2e-05
* train\_batch\_size: 8
* eval\_batch\_size: 24
* seed: 1799
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10


### Training results



### Framework versions


* Transformers 4.18.0
* Pytorch 1.10.0+cu111
* Datasets 2.5.1
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 8
* eval\_batch\_size: 24
* seed: 1799
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10 ### Training results ### Framework versions


* Transformers 4.18.0
* Pytorch 1.10.0+cu111
* Datasets 2.5.1
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #t5 #text2text-generation #generated_from_trainer #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 8
* eval\_batch\_size: 24
* seed: 1799
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10 ### Training results ### Framework versions


* Transformers 4.18.0
* Pytorch 1.10.0+cu111
* Datasets 2.5.1
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #t5 #text2text-generation #generated_from_trainer #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 8
* eval\_batch\_size: 24
* seed: 1799
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10### Training results### Framework versions


* Transformers 4.18.0
* Pytorch 1.10.0+cu111
* Datasets 2.5.1
* Tokenizers 0.12.1