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# flan-t5-large-da-multiwoz2.0_400-ep10-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: 0.3642
- Accuracy: 40.0483
- Num: 7358
- Gen Len: 15.3939

## 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: 32
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:----:|:-------:|
| 1.3288        | 0.58  | 200  | 0.5718          | 27.6241  | 7358 | 13.9315 |
| 0.5941        | 1.17  | 400  | 0.4745          | 32.0484  | 7358 | 14.2517 |
| 0.5213        | 1.75  | 600  | 0.4283          | 33.6716  | 7358 | 15.1218 |
| 0.4891        | 2.33  | 800  | 0.4063          | 34.1115  | 7358 | 14.8005 |
| 0.4503        | 2.92  | 1000 | 0.3935          | 35.9067  | 7358 | 15.9095 |
| 0.4213        | 3.5   | 1200 | 0.3833          | 37.2591  | 7358 | 16.0005 |
| 0.4184        | 4.08  | 1400 | 0.3795          | 37.696   | 7358 | 15.478  |
| 0.3959        | 4.66  | 1600 | 0.3762          | 37.401   | 7358 | 14.8752 |
| 0.3847        | 5.25  | 1800 | 0.3714          | 37.7347  | 7358 | 15.9304 |
| 0.3779        | 5.83  | 2000 | 0.3710          | 38.6814  | 7358 | 14.9257 |
| 0.3776        | 6.41  | 2200 | 0.3681          | 38.4266  | 7358 | 15.2517 |
| 0.3601        | 7.0   | 2400 | 0.3669          | 38.6749  | 7358 | 15.1791 |
| 0.3504        | 7.58  | 2600 | 0.3669          | 39.2748  | 7358 | 15.4308 |
| 0.3568        | 8.16  | 2800 | 0.3650          | 39.798   | 7358 | 15.8966 |
| 0.3528        | 8.75  | 3000 | 0.3630          | 39.912   | 7358 | 15.4081 |
| 0.3463        | 9.33  | 3200 | 0.3641          | 40.1243  | 7358 | 15.5367 |
| 0.3439        | 9.91  | 3400 | 0.3642          | 40.0567  | 7358 | 15.3842 |


### 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-ep10-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-ep10-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: 0.3642
* Accuracy: 40.0483
* Num: 7358
* Gen Len: 15.3939


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: 32
* 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: 32
* 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: 32
* 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: 32
* 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