
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# t5-small-finetuned-spider

This model was trained from scratch on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1914
- Rouge2 Precision: 0.6349
- Rouge2 Recall: 0.3964
- Rouge2 Fmeasure: 0.4619

## 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: 5e-05
- train_batch_size: 5
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
|:-------------:|:-----:|:-----:|:---------------:|:----------------:|:-------------:|:---------------:|
| 0.2912        | 1.0   | 1120  | 0.2631          | 0.5653           | 0.3537        | 0.4118          |
| 0.2967        | 2.0   | 2240  | 0.2465          | 0.5758           | 0.363         | 0.4209          |
| 0.3106        | 3.0   | 3360  | 0.2372          | 0.5858           | 0.367         | 0.427           |
| 0.2993        | 4.0   | 4480  | 0.2340          | 0.5995           | 0.3791        | 0.4403          |
| 0.2702        | 5.0   | 5600  | 0.2204          | 0.6035           | 0.3786        | 0.4401          |
| 0.2624        | 6.0   | 6720  | 0.2159          | 0.6094           | 0.3807        | 0.4435          |
| 0.2463        | 7.0   | 7840  | 0.2121          | 0.6207           | 0.3911        | 0.4544          |
| 0.2427        | 8.0   | 8960  | 0.2053          | 0.6198           | 0.3886        | 0.452           |
| 0.2336        | 9.0   | 10080 | 0.2014          | 0.6217           | 0.3871        | 0.4518          |
| 0.2256        | 10.0  | 11200 | 0.1980          | 0.6298           | 0.394         | 0.4589          |
| 0.2212        | 11.0  | 12320 | 0.1960          | 0.6304           | 0.3936        | 0.4589          |
| 0.2141        | 12.0  | 13440 | 0.1962          | 0.63             | 0.3939        | 0.4586          |
| 0.2069        | 13.0  | 14560 | 0.1921          | 0.6328           | 0.3942        | 0.4594          |
| 0.2096        | 14.0  | 15680 | 0.1915          | 0.632            | 0.3953        | 0.46            |
| 0.2115        | 15.0  | 16800 | 0.1914          | 0.6349           | 0.3964        | 0.4619          |


### Framework versions

- Transformers 4.19.0
- Pytorch 1.11.0+cu113
- Datasets 2.2.1
- Tokenizers 0.12.1

{"tags": ["generated_from_trainer"], "model-index": [{"name": "t5-small-finetuned-spider", "results": []}]}
transformers pytorch tensorboard t5 text2text-generation generated_from_trainer autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #tensorboard #t5 #text2text-generation #generated_from_trainer #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

t5-small-finetuned-spider
=========================


This model was trained from scratch on an unknown dataset.
It achieves the following results on the evaluation set:


* Loss: 0.1914
* Rouge2 Precision: 0.6349
* Rouge2 Recall: 0.3964
* Rouge2 Fmeasure: 0.4619


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: 5e-05
* train\_batch\_size: 5
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 15


### Training results



### Framework versions


* Transformers 4.19.0
* Pytorch 1.11.0+cu113
* Datasets 2.2.1
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 5
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 15 ### Training results ### Framework versions


* Transformers 4.19.0
* Pytorch 1.11.0+cu113
* Datasets 2.2.1
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #t5 #text2text-generation #generated_from_trainer #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 5
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 15 ### Training results ### Framework versions


* Transformers 4.19.0
* Pytorch 1.11.0+cu113
* Datasets 2.2.1
* Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #tensorboard #t5 #text2text-generation #generated_from_trainer #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 5
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 15### Training results### Framework versions


* Transformers 4.19.0
* Pytorch 1.11.0+cu113
* Datasets 2.2.1
* Tokenizers 0.12.1