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# flan-t5-large-da-multiwoz_1000

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: 0.3538
- Accuracy: 41.3747
- Num: 3689
- Gen Len: 15.5115

## 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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Num  | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:----:|:-------:|
| 1.3315        | 0.24  | 200  | 0.5697          | 25.9543  | 3689 | 14.556  |
| 0.6418        | 0.48  | 400  | 0.4645          | 30.0503  | 3689 | 14.9314 |
| 0.5433        | 0.72  | 600  | 0.4307          | 31.9506  | 3689 | 16.1515 |
| 0.4909        | 0.95  | 800  | 0.4177          | 34.7593  | 3689 | 15.418  |
| 0.4769        | 1.19  | 1000 | 0.3996          | 35.0943  | 3689 | 14.9607 |
| 0.4491        | 1.43  | 1200 | 0.3881          | 36.2741  | 3689 | 15.543  |
| 0.4531        | 1.67  | 1400 | 0.3820          | 35.7704  | 3689 | 14.1583 |
| 0.4322        | 1.91  | 1600 | 0.3726          | 37.4853  | 3689 | 15.961  |
| 0.4188        | 2.15  | 1800 | 0.3699          | 38.4117  | 3689 | 15.0773 |
| 0.4085        | 2.38  | 2000 | 0.3674          | 38.5353  | 3689 | 15.4012 |
| 0.4063        | 2.62  | 2200 | 0.3606          | 40.0046  | 3689 | 15.3546 |
| 0.3977        | 2.86  | 2400 | 0.3570          | 40.6543  | 3689 | 15.704  |
| 0.3992        | 3.1   | 2600 | 0.3549          | 40.4284  | 3689 | 15.7446 |
| 0.3828        | 3.34  | 2800 | 0.3538          | 41.3747  | 3689 | 15.5115 |
| 0.3792        | 3.58  | 3000 | 0.3539          | 39.8513  | 3689 | 14.7951 |
| 0.3914        | 3.81  | 3200 | 0.3498          | 41.0388  | 3689 | 15.4153 |
| 0.3707        | 4.05  | 3400 | 0.3498          | 40.9596  | 3689 | 16.3136 |


### 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-multiwoz_1000", "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-multiwoz\_1000
===============================


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: 0.3538
* Accuracy: 41.3747
* Num: 3689
* Gen Len: 15.5115


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: 5


### 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: 5 ### 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: 5 ### 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: 5### Training results### Framework versions


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