
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# flan-t5-large-da-multiwoz2.0_800-loss-ep50

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: 0.3367
- Accuracy: 42.2298
- Num: 7358
- Gen Len: 15.2759

## 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: 24
- eval_batch_size: 192
- seed: 1799
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Num  | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:----:|:-------:|
| 1.1324        | 0.89  | 200  | 0.4829          | 29.9104  | 7358 | 13.9689 |
| 0.5151        | 1.79  | 400  | 0.4123          | 33.4043  | 7358 | 14.642  |
| 0.4551        | 2.68  | 600  | 0.3829          | 35.7701  | 7358 | 15.1242 |
| 0.4219        | 3.57  | 800  | 0.3643          | 36.7057  | 7358 | 15.3396 |
| 0.3957        | 4.46  | 1000 | 0.3564          | 38.4778  | 7358 | 14.7546 |
| 0.3794        | 5.36  | 1200 | 0.3535          | 39.5482  | 7358 | 15.7898 |
| 0.3691        | 6.25  | 1400 | 0.3462          | 40.9266  | 7358 | 15.1525 |
| 0.3572        | 7.14  | 1600 | 0.3433          | 41.2441  | 7358 | 15.5348 |
| 0.3458        | 8.04  | 1800 | 0.3423          | 41.3965  | 7358 | 15.9547 |
| 0.3383        | 8.93  | 2000 | 0.3367          | 42.2298  | 7358 | 15.2759 |
| 0.3298        | 9.82  | 2200 | 0.3369          | 42.0268  | 7358 | 15.1411 |
| 0.3193        | 10.71 | 2400 | 0.3377          | 42.2034  | 7358 | 15.6401 |
| 0.3126        | 11.61 | 2600 | 0.3403          | 43.2389  | 7358 | 15.657  |
| 0.3049        | 12.5  | 2800 | 0.3380          | 43.1584  | 7358 | 14.8736 |
| 0.3014        | 13.39 | 3000 | 0.3394          | 43.1853  | 7358 | 15.4948 |


### 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_800-loss-ep50", "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\_800-loss-ep50
===========================================


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: 0.3367
* Accuracy: 42.2298
* Num: 7358
* Gen Len: 15.2759


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: 24
* eval\_batch\_size: 192
* seed: 1799
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 50


### 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: 24
* eval\_batch\_size: 192
* seed: 1799
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 50 ### 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: 24
* eval\_batch\_size: 192
* seed: 1799
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 50 ### 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: 24
* eval\_batch\_size: 192
* seed: 1799
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 50### Training results### Framework versions


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