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# flan-t5-large-SQuAD-qag-ep6

This model is a fine-tuned version of [google/flan-t5-large](https://huggingface.co/google/flan-t5-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8670
- Rouge1: 40.8926
- Rouge2: 19.5196
- Rougel: 37.4672
- Rougelsum: 37.4713
- F1: 21.4247
- Exact Match: 15.1427
- Gen Len: 18.3706

## 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: 2e-05
- train_batch_size: 24
- eval_batch_size: 48
- seed: 1799
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 6

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | F1      | Exact Match | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|:-----------:|:-------:|
| 1.0439        | 0.51  | 400  | 0.8849          | 39.8979 | 18.5242 | 36.3173 | 36.3341   | 20.5015 | 13.8365     | 18.4069 |
| 0.9761        | 1.02  | 800  | 0.8748          | 40.0168 | 18.6616 | 36.6103 | 36.6343   | 19.4625 | 13.9332     | 18.4359 |
| 0.9358        | 1.52  | 1200 | 0.8709          | 40.6382 | 19.6212 | 37.2797 | 37.3127   | 20.2207 | 14.2235     | 18.3957 |
| 0.919         | 2.03  | 1600 | 0.8697          | 41.2054 | 20.0197 | 37.7826 | 37.8021   | 21.7337 | 15.4814     | 18.3633 |
| 0.8849        | 2.54  | 2000 | 0.8695          | 41.3385 | 19.9503 | 37.9501 | 37.9707   | 22.0787 | 15.6265     | 18.3507 |
| 0.8869        | 3.05  | 2400 | 0.8674          | 41.2089 | 19.7348 | 37.6962 | 37.7184   | 21.3812 | 14.9492     | 18.4122 |
| 0.8617        | 3.56  | 2800 | 0.8670          | 40.8926 | 19.5196 | 37.4672 | 37.4713   | 21.4247 | 15.1427     | 18.3706 |
| 0.8486        | 4.07  | 3200 | 0.8678          | 40.856  | 19.6152 | 37.4585 | 37.4462   | 22.0102 | 15.5781     | 18.3522 |
| 0.8367        | 4.57  | 3600 | 0.8678          | 40.9533 | 19.7798 | 37.5764 | 37.5818   | 21.769  | 15.7233     | 18.328  |
| 0.8442        | 5.08  | 4000 | 0.8671          | 41.2103 | 19.987  | 37.8326 | 37.8498   | 22.3873 | 16.1587     | 18.3314 |
| 0.8317        | 5.59  | 4400 | 0.8673          | 41.0444 | 19.7886 | 37.6754 | 37.6706   | 22.0032 | 15.7716     | 18.3208 |


### Framework versions

- Transformers 4.18.0
- Pytorch 1.11.0+cu113
- Datasets 2.5.1
- Tokenizers 0.12.1

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["rouge", "f1"], "model-index": [{"name": "flan-t5-large-SQuAD-qag-ep6", "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 

flan-t5-large-SQuAD-qag-ep6
===========================


This model is a fine-tuned version of google/flan-t5-large on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 0.8670
* Rouge1: 40.8926
* Rouge2: 19.5196
* Rougel: 37.4672
* Rougelsum: 37.4713
* F1: 21.4247
* Exact Match: 15.1427
* Gen Len: 18.3706


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: 2e-05
* train\_batch\_size: 24
* eval\_batch\_size: 48
* seed: 1799
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 6


### Training results



### Framework versions


* Transformers 4.18.0
* Pytorch 1.11.0+cu113
* Datasets 2.5.1
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 24
* eval\_batch\_size: 48
* seed: 1799
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 6 ### Training results ### Framework versions


* Transformers 4.18.0
* Pytorch 1.11.0+cu113
* Datasets 2.5.1
* Tokenizers 0.12.1
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: 2e-05
* train\_batch\_size: 24
* eval\_batch\_size: 48
* seed: 1799
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 6 ### Training results ### Framework versions


* Transformers 4.18.0
* Pytorch 1.11.0+cu113
* Datasets 2.5.1
* Tokenizers 0.12.1