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# flan-t5-large-da-multiwoz2.1_800-ep20-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: 0.3425
- Accuracy: 43.5925
- Num: 7365
- Gen Len: 15.6426

## 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: 16
- eval_batch_size: 64
- seed: 1799
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Num  | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:----:|:-------:|
| 0.8715        | 1.19  | 400  | 0.4399          | 33.0885  | 7365 | 16.6641 |
| 0.4615        | 2.38  | 800  | 0.3853          | 35.0673  | 7365 | 14.4206 |
| 0.4139        | 3.57  | 1200 | 0.3576          | 37.9691  | 7365 | 16.1995 |
| 0.3802        | 4.76  | 1600 | 0.3539          | 39.7252  | 7365 | 15.447  |
| 0.3643        | 5.95  | 2000 | 0.3436          | 40.0614  | 7365 | 15.7359 |
| 0.347         | 7.14  | 2400 | 0.3438          | 41.028   | 7365 | 15.2403 |
| 0.3351        | 8.33  | 2800 | 0.3392          | 42.0823  | 7365 | 15.7405 |
| 0.3269        | 9.52  | 3200 | 0.3372          | 42.2902  | 7365 | 15.7686 |
| 0.3165        | 10.71 | 3600 | 0.3381          | 42.3669  | 7365 | 15.4957 |
| 0.3093        | 11.9  | 4000 | 0.3405          | 42.9291  | 7365 | 15.6539 |
| 0.3018        | 13.1  | 4400 | 0.3421          | 42.9564  | 7365 | 15.8058 |
| 0.2962        | 14.29 | 4800 | 0.3381          | 43.2625  | 7365 | 15.5039 |
| 0.2893        | 15.48 | 5200 | 0.3424          | 43.5069  | 7365 | 15.608  |
| 0.2866        | 16.67 | 5600 | 0.3426          | 43.3565  | 7365 | 15.7112 |
| 0.2817        | 17.86 | 6000 | 0.3434          | 43.6685  | 7365 | 15.6191 |
| 0.2802        | 19.05 | 6400 | 0.3423          | 43.6242  | 7365 | 15.6804 |


### 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-ep20-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-multiwoz2.1\_800-ep20-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: 0.3425
* Accuracy: 43.5925
* Num: 7365
* Gen Len: 15.6426


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: 16
* eval\_batch\_size: 64
* seed: 1799
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 20


### 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: 16
* eval\_batch\_size: 64
* seed: 1799
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 20 ### 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: 16
* eval\_batch\_size: 64
* seed: 1799
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 20 ### 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: 16
* eval\_batch\_size: 64
* seed: 1799
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 20### Training results### Framework versions


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