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# flan-t5-large-da-multiwoz2.1_fs0.2

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: 0.3159
- Accuracy: 45.1554
- Num: 3689
- Gen Len: 15.5213

## 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 | Accuracy | Num  | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:----:|:-------:|
| 0.9653        | 0.28  | 400  | 0.4635          | 31.3166  | 3689 | 15.196  |
| 0.5071        | 0.57  | 800  | 0.4031          | 35.8289  | 3689 | 15.6546 |
| 0.4603        | 0.85  | 1200 | 0.3718          | 37.6313  | 3689 | 15.6511 |
| 0.4219        | 1.13  | 1600 | 0.3577          | 37.9333  | 3689 | 16.5319 |
| 0.3991        | 1.42  | 2000 | 0.3491          | 40.5462  | 3689 | 15.453  |
| 0.394         | 1.7   | 2400 | 0.3409          | 40.9333  | 3689 | 15.5137 |
| 0.3822        | 1.98  | 2800 | 0.3370          | 41.2932  | 3689 | 15.225  |
| 0.3625        | 2.26  | 3200 | 0.3327          | 42.1132  | 3689 | 16.0718 |
| 0.3577        | 2.55  | 3600 | 0.3329          | 42.1372  | 3689 | 15.9973 |
| 0.3644        | 2.83  | 4000 | 0.3303          | 42.2529  | 3689 | 15.6525 |
| 0.349         | 3.11  | 4400 | 0.3256          | 43.2025  | 3689 | 15.6601 |
| 0.3355        | 3.4   | 4800 | 0.3243          | 43.791   | 3689 | 15.5451 |
| 0.338         | 3.68  | 5200 | 0.3231          | 43.5073  | 3689 | 15.7411 |
| 0.3424        | 3.96  | 5600 | 0.3196          | 44.5281  | 3689 | 15.1307 |
| 0.3299        | 4.25  | 6000 | 0.3159          | 45.1554  | 3689 | 15.5213 |
| 0.328         | 4.53  | 6400 | 0.3188          | 43.4699  | 3689 | 15.3849 |
| 0.3204        | 4.81  | 6800 | 0.3159          | 44.7764  | 3689 | 15.8219 |
| 0.3166        | 5.1   | 7200 | 0.3165          | 45.0608  | 3689 | 15.8791 |


### 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_fs0.2", "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\_fs0.2
===================================


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: 0.3159
* Accuracy: 45.1554
* Num: 3689
* Gen Len: 15.5213


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 #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: 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 #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: 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