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# t5-end2end-questions-generation_2

This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6223

## 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: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 7

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 2.7103        | 0.13  | 10   | 1.7584          |
| 1.8298        | 0.26  | 20   | 1.3377          |
| 1.4424        | 0.39  | 30   | 1.1610          |
| 1.4063        | 0.52  | 40   | 1.0564          |
| 1.2738        | 0.65  | 50   | 1.0332          |
| 1.2477        | 0.78  | 60   | 0.9531          |
| 1.146         | 0.91  | 70   | 0.9050          |
| 1.0134        | 1.04  | 80   | 0.9388          |
| 0.8782        | 1.17  | 90   | 0.9215          |
| 0.8869        | 1.3   | 100  | 0.8930          |
| 0.8963        | 1.43  | 110  | 0.8996          |
| 0.9138        | 1.56  | 120  | 0.8616          |
| 0.7963        | 1.69  | 130  | 0.8060          |
| 0.8611        | 1.82  | 140  | 0.7611          |
| 1.0504        | 1.95  | 150  | 0.7606          |
| 0.6802        | 2.08  | 160  | 0.7791          |
| 0.7488        | 2.21  | 170  | 0.7470          |
| 0.6659        | 2.34  | 180  | 0.7367          |
| 0.7061        | 2.47  | 190  | 0.7194          |
| 0.6771        | 2.6   | 200  | 0.7006          |
| 0.7267        | 2.73  | 210  | 0.6858          |
| 0.7251        | 2.86  | 220  | 0.6797          |
| 0.7426        | 2.99  | 230  | 0.6877          |
| 0.5425        | 3.12  | 240  | 0.6994          |
| 0.5298        | 3.25  | 250  | 0.7096          |
| 0.697         | 3.38  | 260  | 0.6941          |
| 0.5643        | 3.51  | 270  | 0.6534          |
| 0.6983        | 3.64  | 280  | 0.6407          |
| 0.587         | 3.77  | 290  | 0.6404          |
| 0.6487        | 3.9   | 300  | 0.6489          |
| 0.5862        | 4.03  | 310  | 0.6567          |
| 0.5524        | 4.16  | 320  | 0.6610          |
| 0.5432        | 4.29  | 330  | 0.6609          |
| 0.5165        | 4.42  | 340  | 0.6558          |
| 0.5248        | 4.55  | 350  | 0.6387          |
| 0.5322        | 4.68  | 360  | 0.6319          |
| 0.5272        | 4.81  | 370  | 0.6214          |
| 0.5555        | 4.94  | 380  | 0.6252          |
| 0.597         | 5.06  | 390  | 0.6281          |
| 0.5745        | 5.19  | 400  | 0.6283          |
| 0.5156        | 5.32  | 410  | 0.6265          |
| 0.4898        | 5.45  | 420  | 0.6307          |
| 0.543         | 5.58  | 430  | 0.6280          |
| 0.5094        | 5.71  | 440  | 0.6295          |
| 0.5023        | 5.84  | 450  | 0.6279          |
| 0.4483        | 5.97  | 460  | 0.6228          |
| 0.5134        | 6.1   | 470  | 0.6239          |
| 0.5054        | 6.23  | 480  | 0.6230          |
| 0.4632        | 6.36  | 490  | 0.6205          |
| 0.5016        | 6.49  | 500  | 0.6212          |
| 0.4838        | 6.62  | 510  | 0.6219          |
| 0.4613        | 6.75  | 520  | 0.6225          |
| 0.5062        | 6.88  | 530  | 0.6223          |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.1+cu117
- Datasets 2.12.0
- Tokenizers 0.13.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "model-index": [{"name": "t5-end2end-questions-generation_2", "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 

t5-end2end-questions-generation\_2
==================================


This model is a fine-tuned version of t5-base on an unknown dataset.
It achieves the following results on the evaluation set:


* Loss: 0.6223


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: 1
* eval\_batch\_size: 1
* seed: 42
* gradient\_accumulation\_steps: 4
* total\_train\_batch\_size: 4
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 7


### Training results



### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.1+cu117
* Datasets 2.12.0
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0001
* train\_batch\_size: 1
* eval\_batch\_size: 1
* seed: 42
* gradient\_accumulation\_steps: 4
* total\_train\_batch\_size: 4
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 7 ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.1+cu117
* Datasets 2.12.0
* Tokenizers 0.13.3
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: 0.0001
* train\_batch\_size: 1
* eval\_batch\_size: 1
* seed: 42
* gradient\_accumulation\_steps: 4
* total\_train\_batch\_size: 4
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 7 ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.1+cu117
* Datasets 2.12.0
* Tokenizers 0.13.3