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# flan-t5-base-da-multiwoz2.1_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: 0.3479
- Accuracy: 41.5609
- Num: 7365
- Gen Len: 15.8372

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:----:|:-------:|
| 1.3224        | 2.22  | 200  | 0.5297          | 27.7246  | 7365 | 15.4379 |
| 0.581         | 4.44  | 400  | 0.4345          | 33.0547  | 7365 | 15.4058 |
| 0.498         | 6.67  | 600  | 0.4021          | 34.9997  | 7365 | 15.9775 |
| 0.4625        | 8.89  | 800  | 0.3876          | 35.7346  | 7365 | 15.8725 |
| 0.4381        | 11.11 | 1000 | 0.3764          | 36.9032  | 7365 | 15.7621 |
| 0.4194        | 13.33 | 1200 | 0.3688          | 37.7098  | 7365 | 16.0453 |
| 0.4061        | 15.56 | 1400 | 0.3642          | 38.3643  | 7365 | 15.5204 |
| 0.3939        | 17.78 | 1600 | 0.3600          | 38.8761  | 7365 | 15.1166 |
| 0.3811        | 20.0  | 1800 | 0.3563          | 39.153   | 7365 | 15.5255 |
| 0.3736        | 22.22 | 2000 | 0.3544          | 39.9885  | 7365 | 15.9825 |
| 0.3656        | 24.44 | 2200 | 0.3532          | 39.9766  | 7365 | 15.4758 |
| 0.356         | 26.67 | 2400 | 0.3503          | 40.2686  | 7365 | 15.8242 |
| 0.3525        | 28.89 | 2600 | 0.3484          | 41.0194  | 7365 | 15.8925 |
| 0.3463        | 31.11 | 2800 | 0.3484          | 40.7746  | 7365 | 15.8033 |
| 0.3386        | 33.33 | 3000 | 0.3483          | 40.5603  | 7365 | 15.7708 |
| 0.3341        | 35.56 | 3200 | 0.3489          | 41.2147  | 7365 | 15.9707 |
| 0.3291        | 37.78 | 3400 | 0.3485          | 41.4603  | 7365 | 15.8473 |
| 0.3232        | 40.0  | 3600 | 0.3479          | 41.5609  | 7365 | 15.8372 |
| 0.3188        | 42.22 | 3800 | 0.3488          | 41.499   | 7365 | 15.8732 |
| 0.3142        | 44.44 | 4000 | 0.3484          | 41.7224  | 7365 | 15.6745 |
| 0.3104        | 46.67 | 4200 | 0.3497          | 41.8095  | 7365 | 15.9066 |
| 0.3079        | 48.89 | 4400 | 0.3495          | 41.8793  | 7365 | 15.7776 |
| 0.304         | 51.11 | 4600 | 0.3516          | 42.1058  | 7365 | 15.9699 |


### 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-multiwoz2.1_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-multiwoz2.1\_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: 0.3479
* Accuracy: 41.5609
* Num: 7365
* Gen Len: 15.8372


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