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# t5-large-SQuAD-qag-ep6

This model is a fine-tuned version of [t5-large](https://huggingface.co/t5-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8950
- Rouge1: 41.0251
- Rouge2: 19.2729
- Rougel: 37.4514
- Rougelsum: 37.4839
- F1: 20.0159
- Exact Match: 14.2719
- Gen Len: 18.418

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|:-----------:|:-------:|
| 1.1752        | 0.51  | 400  | 0.9542          | 39.054  | 17.5678 | 35.471  | 35.4744   | 16.7879 | 10.8853     | 18.5186 |
| 1.0232        | 1.02  | 800  | 0.9232          | 40.062  | 18.493  | 36.4108 | 36.4335   | 18.7316 | 12.9173     | 18.4543 |
| 0.9641        | 1.52  | 1200 | 0.9112          | 40.6835 | 19.0484 | 37.0867 | 37.1329   | 19.3326 | 14.03       | 18.4078 |
| 0.9422        | 2.03  | 1600 | 0.9044          | 40.9087 | 19.2513 | 37.3069 | 37.3196   | 19.999  | 14.2719     | 18.4383 |
| 0.8989        | 2.54  | 2000 | 0.9026          | 41.0666 | 19.4921 | 37.4916 | 37.5115   | 21.0451 | 14.8041     | 18.3469 |
| 0.9015        | 3.05  | 2400 | 0.8986          | 40.471  | 18.8468 | 36.9384 | 36.9357   | 19.3467 | 13.8365     | 18.4557 |
| 0.8679        | 3.56  | 2800 | 0.8950          | 41.0251 | 19.2729 | 37.4514 | 37.4839   | 20.0159 | 14.2719     | 18.418  |
| 0.8521        | 4.07  | 3200 | 0.8982          | 41.1633 | 19.6433 | 37.6253 | 37.6541   | 21.0075 | 15.046      | 18.3807 |
| 0.8362        | 4.57  | 3600 | 0.8972          | 40.9127 | 19.4618 | 37.4    | 37.4431   | 20.9531 | 14.8524     | 18.3503 |
| 0.8415        | 5.08  | 4000 | 0.8970          | 41.2265 | 19.7241 | 37.7405 | 37.7653   | 21.5704 | 15.1911     | 18.388  |
| 0.8312        | 5.59  | 4400 | 0.8966          | 40.9824 | 19.4891 | 37.533  | 37.5485   | 20.8781 | 14.7073     | 18.3967 |


### 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": "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 

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


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


* Loss: 0.8950
* Rouge1: 41.0251
* Rouge2: 19.2729
* Rougel: 37.4514
* Rougelsum: 37.4839
* F1: 20.0159
* Exact Match: 14.2719
* Gen Len: 18.418


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