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# flan-t5-base-SQuAD-qag-ep12

This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9491
- Rouge1: 39.8393
- Rouge2: 18.8838
- Rougel: 36.5176
- Rougelsum: 36.5411
- F1: 19.9955
- Exact Match: 13.8849
- Gen Len: 18.4103

## 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: 72
- eval_batch_size: 144
- seed: 1799
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 12

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | F1      | Exact Match | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|:-----------:|:-------:|
| 1.2248        | 0.76  | 200  | 0.9934          | 38.669  | 17.2616 | 35.2097 | 35.2505   | 17.2799 | 12.0464     | 18.5138 |
| 1.1059        | 1.52  | 400  | 0.9766          | 38.6953 | 17.255  | 35.1034 | 35.1485   | 16.7969 | 12.0464     | 18.5167 |
| 1.0784        | 2.28  | 600  | 0.9667          | 38.2853 | 17.165  | 34.8432 | 34.8858   | 17.5185 | 12.5786     | 18.4906 |
| 1.0628        | 3.04  | 800  | 0.9635          | 38.7413 | 17.4317 | 35.2968 | 35.3255   | 17.8293 | 12.6754     | 18.4751 |
| 1.0498        | 3.8   | 1000 | 0.9586          | 39.4263 | 18.0546 | 35.9042 | 35.9572   | 18.8349 | 13.4011     | 18.4475 |
| 1.0264        | 4.56  | 1200 | 0.9574          | 39.3702 | 17.9767 | 35.8919 | 35.9221   | 18.8685 | 13.1592     | 18.4272 |
| 1.0282        | 5.32  | 1400 | 0.9546          | 39.395  | 18.2361 | 35.9973 | 36.0321   | 19.2805 | 13.4494     | 18.4272 |
| 1.0119        | 6.08  | 1600 | 0.9550          | 39.3239 | 18.2565 | 35.9434 | 35.9944   | 19.2463 | 13.5946     | 18.4272 |
| 1.0022        | 6.84  | 1800 | 0.9526          | 39.6112 | 18.4996 | 36.1855 | 36.2362   | 19.7996 | 13.9816     | 18.4107 |
| 1.0           | 7.6   | 2000 | 0.9516          | 39.6419 | 18.5781 | 36.2251 | 36.2741   | 19.7594 | 13.6913     | 18.3991 |
| 0.9946        | 8.37  | 2200 | 0.9509          | 39.536  | 18.4871 | 36.1189 | 36.1826   | 19.6993 | 13.5462     | 18.4224 |
| 0.9888        | 9.13  | 2400 | 0.9503          | 39.7414 | 18.6988 | 36.3305 | 36.3656   | 19.8152 | 13.6913     | 18.4286 |
| 0.9838        | 9.89  | 2600 | 0.9500          | 39.9269 | 18.8588 | 36.5126 | 36.5534   | 19.9364 | 13.9332     | 18.4136 |
| 0.987         | 10.65 | 2800 | 0.9491          | 39.8393 | 18.8838 | 36.5176 | 36.5411   | 19.9955 | 13.8849     | 18.4103 |
| 0.9809        | 11.41 | 3000 | 0.9494          | 39.7507 | 18.6815 | 36.348  | 36.3761   | 19.7615 | 13.7397     | 18.4112 |


### 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-base-SQuAD-qag-ep12", "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-base-SQuAD-qag-ep12
===========================


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


* Loss: 0.9491
* Rouge1: 39.8393
* Rouge2: 18.8838
* Rougel: 36.5176
* Rougelsum: 36.5411
* F1: 19.9955
* Exact Match: 13.8849
* Gen Len: 18.4103


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: 72
* eval\_batch\_size: 144
* seed: 1799
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 12


### 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: 72
* eval\_batch\_size: 144
* seed: 1799
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 12 ### 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: 72
* eval\_batch\_size: 144
* seed: 1799
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 12 ### Training results ### Framework versions


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