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# t5-small-qg-2.0

This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the the_squad_qg dataset.
It achieves the following results on the evaluation set:
- Loss: 1.9589

## 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: 0.0001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 3.2981        | 0.68  | 100  | 2.3598          |
| 2.4962        | 1.36  | 200  | 2.2479          |
| 2.374         | 2.03  | 300  | 2.1625          |
| 2.2951        | 2.71  | 400  | 2.0871          |
| 2.2279        | 3.39  | 500  | 2.0532          |
| 2.1926        | 4.07  | 600  | 2.0325          |
| 2.1605        | 4.75  | 700  | 2.0154          |
| 2.1438        | 5.42  | 800  | 1.9920          |
| 2.1154        | 6.1   | 900  | 1.9829          |
| 2.1014        | 6.78  | 1000 | 1.9782          |
| 2.0976        | 7.46  | 1100 | 1.9649          |
| 2.0817        | 8.14  | 1200 | 1.9647          |
| 2.0767        | 8.81  | 1300 | 1.9631          |
| 2.0749        | 9.49  | 1400 | 1.9589          |


### Framework versions

- Transformers 4.27.3
- Pytorch 2.0.0
- Datasets 2.10.1
- Tokenizers 0.11.0

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["the_squad_qg"], "model-index": [{"name": "t5-small-qg-2.0", "results": []}]}
transformers pytorch t5 text2text-generation generated_from_trainer dataset:the_squad_qg license:apache-2.0 autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #t5 #text2text-generation #generated_from_trainer #dataset-the_squad_qg #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

t5-small-qg-2.0
===============


This model is a fine-tuned version of t5-small on the the\_squad\_qg dataset.
It achieves the following results on the evaluation set:


* Loss: 1.9589


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: 0.0001
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 16
* total\_train\_batch\_size: 128
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.27.3
* Pytorch 2.0.0
* Datasets 2.10.1
* Tokenizers 0.11.0



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0001
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 16
* total\_train\_batch\_size: 128
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.27.3
* Pytorch 2.0.0
* Datasets 2.10.1
* Tokenizers 0.11.0
TAGS
#transformers #pytorch #t5 #text2text-generation #generated_from_trainer #dataset-the_squad_qg #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0001
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 16
* total\_train\_batch\_size: 128
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.27.3
* Pytorch 2.0.0
* Datasets 2.10.1
* Tokenizers 0.11.0
TAGS
#transformers #pytorch #t5 #text2text-generation #generated_from_trainer #dataset-the_squad_qg #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0001
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 16
* total\_train\_batch\_size: 128
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.27.3
* Pytorch 2.0.0
* Datasets 2.10.1
* Tokenizers 0.11.0