
<!-- 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. -->

# flan-t5-base-qg-SQuAD-LMQG

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: 0.5624
- Rouge1: 52.9376
- Rouge2: 30.3418
- Rougel: 48.9442
- Rougelsum: 48.9337
- Meteor: 48.0417
- Bleu-n: 21.5099
- Bleu-1: 53.2950
- Bleu-2: 27.3888
- Bleu-3: 17.6196
- Bleu-4: 11.8132
- Gen Len: 14.2609

## 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
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|:-------:|:-------:|:-------:|:-------:|:-------:|:-------:|
| 0.6054        | 1.0   | 9466  | 0.5603          | 51.5022 | 28.8098 | 47.624  | 47.6181   | 46.3462 | 20.5165 | 52.2978 | 26.2204 | 16.7816 | 11.2230 | 14.1466 |
| 0.5436        | 2.0   | 18932 | 0.5555          | 52.6557 | 29.8173 | 48.7211 | 48.7146   | 47.4380 | 21.0460 | 53.6907 | 27.3374 | 17.4950 | 11.6865 | 14.0910 |
| 0.5087        | 3.0   | 28398 | 0.5572          | 52.5567 | 30.0117 | 48.5798 | 48.5669   | 47.5632 | 21.3178 | 53.1790 | 27.2268 | 17.5366 | 11.8127 | 14.1871 |
| 0.4874        | 4.0   | 37864 | 0.5601          | 52.9404 | 30.3445 | 48.9746 | 48.9583   | 47.9995 | 21.5205 | 53.3457 | 27.4082 | 17.6273 | 11.8327 | 14.2623 |
| 0.473         | 5.0   | 47330 | 0.5624          | 52.9376 | 30.3418 | 48.9442 | 48.9337   | 48.0417 | 21.5099 | 53.2950 | 27.3888 | 17.6196 | 11.8132 | 14.2609 |


### 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-qg-SQuAD-LMQG", "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": 52.9376, "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-qg-SQuAD-LMQG
==========================


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: 0.5624
* Rouge1: 52.9376
* Rouge2: 30.3418
* Rougel: 48.9442
* Rougelsum: 48.9337
* Meteor: 48.0417
* Bleu-n: 21.5099
* Bleu-1: 53.2950
* Bleu-2: 27.3888
* Bleu-3: 17.6196
* Bleu-4: 11.8132
* Gen Len: 14.2609


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
* 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
* 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
* 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