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# flan-t5-large-da-multiwoz2.1_400

This model is a fine-tuned version of [google/flan-t5-large](https://huggingface.co/google/flan-t5-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3640
- Accuracy: 41.5248
- Num: 3689
- Gen Len: 15.72

## 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: 16
- eval_batch_size: 48
- seed: 1799
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Num  | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:----:|:-------:|
| 1.182         | 1.16  | 200  | 0.5116          | 29.9369  | 3689 | 13.7774 |
| 0.5435        | 2.33  | 400  | 0.4323          | 33.5836  | 3689 | 15.3494 |
| 0.4654        | 3.49  | 600  | 0.3987          | 35.5517  | 3689 | 15.91   |
| 0.4345        | 4.65  | 800  | 0.3823          | 37.6767  | 3689 | 15.8986 |
| 0.4054        | 5.81  | 1000 | 0.3725          | 38.6302  | 3689 | 15.19   |
| 0.3883        | 6.98  | 1200 | 0.3689          | 38.7642  | 3689 | 15.7896 |
| 0.3694        | 8.14  | 1400 | 0.3685          | 40.0178  | 3689 | 16.3613 |
| 0.3573        | 9.3   | 1600 | 0.3639          | 40.4155  | 3689 | 15.614  |
| 0.3465        | 10.47 | 1800 | 0.3633          | 40.8682  | 3689 | 15.9461 |
| 0.3404        | 11.63 | 2000 | 0.3631          | 40.4788  | 3689 | 16.0949 |
| 0.329         | 12.79 | 2200 | 0.3617          | 41.5163  | 3689 | 15.434  |
| 0.3176        | 13.95 | 2400 | 0.3662          | 41.2127  | 3689 | 15.8075 |
| 0.3129        | 15.12 | 2600 | 0.3665          | 41.2478  | 3689 | 15.5636 |
| 0.3153        | 16.28 | 2800 | 0.3648          | 41.0925  | 3689 | 15.6617 |
| 0.3073        | 17.44 | 3000 | 0.3644          | 41.276   | 3689 | 15.7137 |
| 0.3003        | 18.6  | 3200 | 0.3640          | 41.5248  | 3689 | 15.72   |
| 0.2988        | 19.77 | 3400 | 0.3651          | 41.4459  | 3689 | 15.7322 |


### Framework versions

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

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "model-index": [{"name": "flan-t5-large-da-multiwoz2.1_400", "results": []}]}
transformers pytorch t5 text2text-generation generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #t5 #text2text-generation #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

flan-t5-large-da-multiwoz2.1\_400
=================================


This model is a fine-tuned version of google/flan-t5-large on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 0.3640
* Accuracy: 41.5248
* Num: 3689
* Gen Len: 15.72


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: 16
* eval\_batch\_size: 48
* seed: 1799
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 20


### 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: 16
* eval\_batch\_size: 48
* seed: 1799
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 20 ### 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 #license-apache-2.0 #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: 16
* eval\_batch\_size: 48
* seed: 1799
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 20 ### 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 #license-apache-2.0 #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: 16
* eval\_batch\_size: 48
* seed: 1799
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 20### Training results### Framework versions


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