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# flan-t5-large-da-multiwoz2.0_400-ep20-nonstop

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: 0.3661
- Accuracy: 41.2421
- Num: 7358
- Gen Len: 15.5222

## 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: 64
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:----:|:-------:|
| 1.1824        | 1.16  | 200  | 0.5187          | 28.4524  | 7358 | 14.7642 |
| 0.5471        | 2.33  | 400  | 0.4278          | 32.5629  | 7358 | 15.4386 |
| 0.4647        | 3.49  | 600  | 0.4029          | 35.2443  | 7358 | 16.135  |
| 0.4313        | 4.65  | 800  | 0.3820          | 36.6479  | 7358 | 16.1552 |
| 0.4074        | 5.81  | 1000 | 0.3775          | 37.6957  | 7358 | 15.1439 |
| 0.3859        | 6.98  | 1200 | 0.3690          | 38.3142  | 7358 | 15.2045 |
| 0.369         | 8.14  | 1400 | 0.3720          | 39.8799  | 7358 | 15.7923 |
| 0.3547        | 9.3   | 1600 | 0.3665          | 39.5217  | 7358 | 15.3394 |
| 0.3457        | 10.47 | 1800 | 0.3632          | 39.8289  | 7358 | 15.4761 |
| 0.3423        | 11.63 | 2000 | 0.3678          | 39.9509  | 7358 | 15.6708 |
| 0.3295        | 12.79 | 2200 | 0.3657          | 41.1373  | 7358 | 15.1586 |
| 0.3212        | 13.95 | 2400 | 0.3651          | 40.8611  | 7358 | 15.7312 |
| 0.3128        | 15.12 | 2600 | 0.3664          | 40.8806  | 7358 | 15.4553 |
| 0.3131        | 16.28 | 2800 | 0.3677          | 40.8906  | 7358 | 15.4629 |
| 0.3093        | 17.44 | 3000 | 0.3661          | 40.9971  | 7358 | 15.4329 |
| 0.3021        | 18.6  | 3200 | 0.3652          | 41.2953  | 7358 | 15.5118 |
| 0.3004        | 19.77 | 3400 | 0.3661          | 41.2492  | 7358 | 15.5246 |


### 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-multiwoz2.0_400-ep20-nonstop", "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-multiwoz2.0\_400-ep20-nonstop
==============================================


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: 0.3661
* Accuracy: 41.2421
* Num: 7358
* Gen Len: 15.5222


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: 64
* 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: 64
* 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: 64
* 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: 64
* 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