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# flan-t5-large-da-multiwoz2.1_800

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: 0.3334
- Accuracy: 44.0942
- Num: 3689
- Gen Len: 15.7842

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:----:|:-------:|
| 1.1927        | 0.6   | 200  | 0.5022          | 31.6941  | 3689 | 15.2413 |
| 0.5504        | 1.19  | 400  | 0.4375          | 33.8508  | 3689 | 16.6571 |
| 0.4773        | 1.79  | 600  | 0.3986          | 34.0235  | 3689 | 14.4118 |
| 0.4458        | 2.38  | 800  | 0.3830          | 35.6435  | 3689 | 14.3944 |
| 0.4241        | 2.98  | 1000 | 0.3654          | 38.1415  | 3689 | 15.0249 |
| 0.4038        | 3.57  | 1200 | 0.3551          | 38.6647  | 3689 | 16.1971 |
| 0.3824        | 4.17  | 1400 | 0.3480          | 39.7139  | 3689 | 15.4738 |
| 0.3781        | 4.76  | 1600 | 0.3512          | 40.5284  | 3689 | 15.4681 |
| 0.3637        | 5.36  | 1800 | 0.3470          | 41.012   | 3689 | 15.6362 |
| 0.3649        | 5.95  | 2000 | 0.3403          | 40.543   | 3689 | 15.7314 |
| 0.3498        | 6.55  | 2200 | 0.3432          | 42.0574  | 3689 | 15.9043 |
| 0.3442        | 7.14  | 2400 | 0.3407          | 41.7062  | 3689 | 15.2239 |
| 0.3381        | 7.74  | 2600 | 0.3386          | 41.9579  | 3689 | 15.3402 |
| 0.3322        | 8.33  | 2800 | 0.3358          | 42.7824  | 3689 | 15.7652 |
| 0.33          | 8.93  | 3000 | 0.3336          | 42.4657  | 3689 | 15.4942 |
| 0.3238        | 9.52  | 3200 | 0.3347          | 42.8539  | 3689 | 15.7726 |
| 0.3162        | 10.12 | 3400 | 0.3371          | 42.9605  | 3689 | 15.3914 |
| 0.3168        | 10.71 | 3600 | 0.3351          | 42.7597  | 3689 | 15.5072 |
| 0.3154        | 11.31 | 3800 | 0.3334          | 44.0942  | 3689 | 15.7842 |
| 0.3032        | 11.9  | 4000 | 0.3375          | 43.5387  | 3689 | 15.656  |
| 0.3032        | 12.5  | 4200 | 0.3363          | 43.7886  | 3689 | 15.3608 |
| 0.3003        | 13.1  | 4400 | 0.3393          | 43.4861  | 3689 | 15.82   |
| 0.2963        | 13.69 | 4600 | 0.3367          | 43.7505  | 3689 | 15.3513 |
| 0.2961        | 14.29 | 4800 | 0.3350          | 43.7886  | 3689 | 15.5232 |


### 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_800", "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\_800
=================================


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: 0.3334
* Accuracy: 44.0942
* Num: 3689
* Gen Len: 15.7842


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