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# flan-t5-large-da-multiwoz2.1_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: 0.3385
- Accuracy: 43.6109
- Num: 7365
- Gen Len: 15.5064

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:----:|:-------:|
| 1.1303        | 0.89  | 200  | 0.4894          | 28.91    | 7365 | 13.4421 |
| 0.5193        | 1.79  | 400  | 0.4112          | 32.6525  | 7365 | 14.586  |
| 0.4567        | 2.68  | 600  | 0.3846          | 35.2014  | 7365 | 15.2893 |
| 0.4231        | 3.57  | 800  | 0.3655          | 36.9293  | 7365 | 15.5405 |
| 0.3955        | 4.46  | 1000 | 0.3582          | 38.2589  | 7365 | 14.8105 |
| 0.3796        | 5.36  | 1200 | 0.3540          | 38.9391  | 7365 | 15.7322 |
| 0.3709        | 6.25  | 1400 | 0.3481          | 40.4378  | 7365 | 14.8407 |
| 0.3561        | 7.14  | 1600 | 0.3451          | 40.4357  | 7365 | 15.2813 |
| 0.3471        | 8.04  | 1800 | 0.3424          | 41.2701  | 7365 | 15.6809 |
| 0.3379        | 8.93  | 2000 | 0.3390          | 41.742   | 7365 | 15.2439 |
| 0.3319        | 9.82  | 2200 | 0.3389          | 41.7948  | 7365 | 15.4334 |
| 0.321         | 10.71 | 2400 | 0.3431          | 41.8954  | 7365 | 15.5404 |
| 0.3153        | 11.61 | 2600 | 0.3402          | 42.7186  | 7365 | 15.7551 |
| 0.3075        | 12.5  | 2800 | 0.3398          | 42.3081  | 7365 | 14.991  |
| 0.3043        | 13.39 | 3000 | 0.3405          | 42.7562  | 7365 | 15.7135 |
| 0.2981        | 14.29 | 3200 | 0.3385          | 43.6109  | 7365 | 15.5064 |
| 0.2912        | 15.18 | 3400 | 0.3430          | 43.2042  | 7365 | 15.4578 |
| 0.2864        | 16.07 | 3600 | 0.3449          | 43.3342  | 7365 | 15.6775 |
| 0.2797        | 16.96 | 3800 | 0.3441          | 43.8748  | 7365 | 15.6739 |
| 0.2738        | 17.86 | 4000 | 0.3477          | 43.7114  | 7365 | 15.7276 |
| 0.268         | 18.75 | 4200 | 0.3464          | 43.4139  | 7365 | 15.3885 |


### 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-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-multiwoz2.1\_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: 0.3385
* Accuracy: 43.6109
* Num: 7365
* Gen Len: 15.5064


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