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# godel_restaurants

This model is a fine-tuned version of [microsoft/GODEL-v1_1-base-seq2seq](https://huggingface.co/microsoft/GODEL-v1_1-base-seq2seq) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2869
- Bleu: 0.0565
- Rouge2: 0.0546
- Rougel: 0.2087

## 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: 1e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- lr_scheduler_warmup_steps: 100
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Bleu   | Rouge2 | Rougel |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|
| 6.0069        | 1.0   | 14   | 5.6691          | 0.0    | 0.0073 | 0.0748 |
| 3.4734        | 2.0   | 28   | 3.0378          | 0.0    | 0.0073 | 0.0637 |
| 1.1689        | 3.0   | 42   | 0.6709          | 0.0    | 0.0065 | 0.0626 |
| 0.523         | 4.0   | 56   | 0.4075          | 0.0    | 0.0065 | 0.0637 |
| 0.4393        | 5.0   | 70   | 0.3495          | 0.0    | 0.0108 | 0.1135 |
| 0.1731        | 6.0   | 84   | 0.3100          | 0.0    | 0.0248 | 0.1499 |
| 0.1428        | 7.0   | 98   | 0.2962          | 0.0    | 0.0582 | 0.1752 |
| 0.1594        | 8.0   | 112  | 0.2931          | 0.0    | 0.0407 | 0.2034 |
| 0.2354        | 9.0   | 126  | 0.2896          | 0.0562 | 0.0546 | 0.21   |
| 0.2704        | 10.0  | 140  | 0.2869          | 0.0565 | 0.0546 | 0.2087 |


### Framework versions

- Transformers 4.27.4
- Pytorch 1.13.1+cu116
- Datasets 2.11.0
- Tokenizers 0.13.2

{"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["bleu"], "model-index": [{"name": "godel_restaurants", "results": []}]}
transformers pytorch t5 text2text-generation generated_from_trainer license:mit autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #t5 #text2text-generation #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

godel\_restaurants
==================


This model is a fine-tuned version of microsoft/GODEL-v1\_1-base-seq2seq on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 0.2869
* Bleu: 0.0565
* Rouge2: 0.0546
* Rougel: 0.2087


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: 1e-05
* train\_batch\_size: 4
* eval\_batch\_size: 4
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: constant
* lr\_scheduler\_warmup\_steps: 100
* num\_epochs: 10


### Training results



### Framework versions


* Transformers 4.27.4
* Pytorch 1.13.1+cu116
* Datasets 2.11.0
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1e-05
* train\_batch\_size: 4
* eval\_batch\_size: 4
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: constant
* lr\_scheduler\_warmup\_steps: 100
* num\_epochs: 10 ### Training results ### Framework versions


* Transformers 4.27.4
* Pytorch 1.13.1+cu116
* Datasets 2.11.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #t5 #text2text-generation #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1e-05
* train\_batch\_size: 4
* eval\_batch\_size: 4
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: constant
* lr\_scheduler\_warmup\_steps: 100
* num\_epochs: 10 ### Training results ### Framework versions


* Transformers 4.27.4
* Pytorch 1.13.1+cu116
* Datasets 2.11.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #t5 #text2text-generation #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1e-05
* train\_batch\_size: 4
* eval\_batch\_size: 4
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: constant
* lr\_scheduler\_warmup\_steps: 100
* num\_epochs: 10### Training results### Framework versions


* Transformers 4.27.4
* Pytorch 1.13.1+cu116
* Datasets 2.11.0
* Tokenizers 0.13.2