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# flan-t5-base-da-multiwoz2.0_800-loss-ep100

This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3457
- Accuracy: 41.0835
- Num: 7358
- Gen Len: 15.8615

## 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: 60
- eval_batch_size: 400
- seed: 1799
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 100

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Num  | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:----:|:-------:|
| 1.3234        | 2.22  | 200  | 0.5277          | 27.6507  | 7358 | 15.1567 |
| 0.5832        | 4.44  | 400  | 0.4297          | 33.2156  | 7358 | 16.0043 |
| 0.4991        | 6.67  | 600  | 0.4029          | 35.309   | 7358 | 16.0595 |
| 0.4618        | 8.89  | 800  | 0.3845          | 36.2347  | 7358 | 15.9841 |
| 0.4372        | 11.11 | 1000 | 0.3750          | 36.6748  | 7358 | 15.6254 |
| 0.4207        | 13.33 | 1200 | 0.3664          | 37.7404  | 7358 | 16.0586 |
| 0.4036        | 15.56 | 1400 | 0.3632          | 38.5822  | 7358 | 15.8968 |
| 0.3929        | 17.78 | 1600 | 0.3588          | 38.4617  | 7358 | 15.1256 |
| 0.3809        | 20.0  | 1800 | 0.3554          | 39.6862  | 7358 | 15.7427 |
| 0.3718        | 22.22 | 2000 | 0.3528          | 40.097   | 7358 | 15.9545 |
| 0.3658        | 24.44 | 2200 | 0.3517          | 39.9142  | 7358 | 15.3572 |
| 0.3581        | 26.67 | 2400 | 0.3486          | 40.6066  | 7358 | 15.7185 |
| 0.3513        | 28.89 | 2600 | 0.3476          | 40.6688  | 7358 | 16.0911 |
| 0.3449        | 31.11 | 2800 | 0.3469          | 41.0736  | 7358 | 15.7513 |
| 0.3395        | 33.33 | 3000 | 0.3457          | 41.0835  | 7358 | 15.8615 |
| 0.3318        | 35.56 | 3200 | 0.3486          | 41.0794  | 7358 | 15.9333 |
| 0.3283        | 37.78 | 3400 | 0.3474          | 41.5949  | 7358 | 16.0735 |
| 0.3229        | 40.0  | 3600 | 0.3476          | 41.8376  | 7358 | 15.7744 |
| 0.3184        | 42.22 | 3800 | 0.3474          | 41.6082  | 7358 | 16.0443 |
| 0.313         | 44.44 | 4000 | 0.3472          | 41.9014  | 7358 | 16.0557 |


### 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-base-da-multiwoz2.0_800-loss-ep100", "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-base-da-multiwoz2.0\_800-loss-ep100
===========================================


This model is a fine-tuned version of google/flan-t5-base on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 0.3457
* Accuracy: 41.0835
* Num: 7358
* Gen Len: 15.8615


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: 60
* eval\_batch\_size: 400
* seed: 1799
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 100


### 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: 60
* eval\_batch\_size: 400
* seed: 1799
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 100 ### 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: 60
* eval\_batch\_size: 400
* seed: 1799
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 100 ### 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: 60
* eval\_batch\_size: 400
* seed: 1799
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 100### Training results### Framework versions


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