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# flan-t5-base-SQuAD-QG

This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on the qg_squad dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5526
- Rouge1: 52.5686
- Rouge2: 29.8958
- Rougel: 48.6057
- Rougelsum: 48.6025
- Meteor: 47.5477
- Bleu-n: 21.1573
- Bleu-1: 53.1650
- Bleu-2: 27.0832
- Bleu-3: 17.3550
- Bleu-4: 11.6241
- Gen Len: 14.2079

## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Meteor  | Bleu-n  | Bleu-1  | Bleu-2  | Bleu-3  | Bleu-4  | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|:-------:|:-------:|:-------:|:-------:|:-------:|:-------:|
| 0.6194        | 1.0   | 2366  | 0.5616          | 51.4072 | 28.7617 | 47.4858 | 47.496    | 46.1739 | 20.4191 | 52.6343 | 26.3347 | 16.8839 | 11.3072 | 14.0406 |
| 0.5727        | 2.0   | 4733  | 0.5540          | 52.0791 | 29.3729 | 48.1664 | 48.1802   | 46.8836 | 20.7120 | 53.2071 | 26.9025 | 17.1791 | 11.4335 | 14.0766 |
| 0.55          | 3.0   | 7099  | 0.5521          | 52.2372 | 29.5935 | 48.2874 | 48.2968   | 47.1455 | 20.9160 | 52.9894 | 26.8627 | 17.2081 | 11.5033 | 14.1710 |
| 0.5293        | 4.0   | 9466  | 0.5523          | 52.5425 | 29.8483 | 48.558  | 48.5627   | 47.4331 | 21.0784 | 53.3308 | 27.1435 | 17.3826 | 11.6385 | 14.1482 |
| 0.5225        | 5.0   | 11830 | 0.5526          | 52.5686 | 29.8958 | 48.6057 | 48.6025   | 47.5477 | 21.1573 | 53.1650 | 27.0832 | 17.3550 | 11.6241 | 14.2079 |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["qg_squad"], "metrics": ["rouge"], "model-index": [{"name": "flan-t5-base-SQuAD-QG", "results": [{"task": {"type": "text2text-generation", "name": "Sequence-to-sequence Language Modeling"}, "dataset": {"name": "qg_squad", "type": "qg_squad", "config": "qg_squad", "split": "validation", "args": "qg_squad"}, "metrics": [{"type": "rouge", "value": 52.5686, "name": "Rouge1"}]}]}]}
transformers pytorch t5 text2text-generation generated_from_trainer dataset:qg_squad license:apache-2.0 model-index autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #t5 #text2text-generation #generated_from_trainer #dataset-qg_squad #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

flan-t5-base-SQuAD-QG
=====================


This model is a fine-tuned version of google/flan-t5-base on the qg\_squad dataset.
It achieves the following results on the evaluation set:


* Loss: 0.5526
* Rouge1: 52.5686
* Rouge2: 29.8958
* Rougel: 48.6057
* Rougelsum: 48.6025
* Meteor: 47.5477
* Bleu-n: 21.1573
* Bleu-1: 53.1650
* Bleu-2: 27.0832
* Bleu-3: 17.3550
* Bleu-4: 11.6241
* Gen Len: 14.2079


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: 8
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 4
* total\_train\_batch\_size: 32
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 5


### Training results



### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0
* Datasets 2.1.0
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 4
* total\_train\_batch\_size: 32
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 5 ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0
* Datasets 2.1.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #t5 #text2text-generation #generated_from_trainer #dataset-qg_squad #license-apache-2.0 #model-index #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: 8
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 4
* total\_train\_batch\_size: 32
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 5 ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0
* Datasets 2.1.0
* Tokenizers 0.13.3