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# flan-t5-large-extraction-cnndm_8000-all

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: 1.6960
- Rouge1: 35.1425
- Rouge2: 15.3877
- Rougel: 30.0992
- Rougelsum: 30.1879
- Gen Len: 19.0

## 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: 8
- eval_batch_size: 24
- seed: 1799
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 2.1837        | 0.2   | 200  | 1.8342          | 33.7673 | 14.4744 | 28.8398 | 28.8415   | 19.0    |
| 1.9557        | 0.4   | 400  | 1.7798          | 34.3577 | 14.8613 | 29.769  | 29.766    | 18.986  |
| 1.9219        | 0.6   | 600  | 1.7428          | 34.8589 | 15.4488 | 30.1084 | 30.1336   | 18.99   |
| 1.871         | 0.8   | 800  | 1.7408          | 35.001  | 15.597  | 30.3374 | 30.37     | 18.99   |
| 1.8729        | 1.0   | 1000 | 1.7502          | 34.9305 | 15.5718 | 30.1495 | 30.1513   | 19.0    |
| 1.7803        | 1.2   | 1200 | 1.7261          | 35.7504 | 15.4172 | 30.6898 | 30.7362   | 19.0    |
| 1.7674        | 1.4   | 1400 | 1.7214          | 35.9564 | 15.6508 | 30.3541 | 30.4292   | 19.0    |
| 1.7704        | 1.6   | 1600 | 1.7253          | 35.2706 | 15.7274 | 30.118  | 30.1324   | 19.0    |
| 1.7656        | 1.8   | 1800 | 1.6960          | 35.1425 | 15.3877 | 30.0992 | 30.1879   | 19.0    |
| 1.7545        | 2.0   | 2000 | 1.7186          | 34.6436 | 15.2712 | 29.9781 | 29.9698   | 19.0    |
| 1.6739        | 2.2   | 2200 | 1.7245          | 35.4083 | 15.8808 | 30.6222 | 30.6752   | 19.0    |
| 1.6836        | 2.4   | 2400 | 1.7212          | 35.1829 | 15.5181 | 30.2438 | 30.262    | 19.0    |


### Framework versions

- Transformers 4.18.0
- Pytorch 1.10.0+cu111
- Datasets 2.5.1
- Tokenizers 0.12.1

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["rouge"], "model-index": [{"name": "flan-t5-large-extraction-cnndm_8000-all", "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-extraction-cnndm\_8000-all
========================================


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: 1.6960
* Rouge1: 35.1425
* Rouge2: 15.3877
* Rougel: 30.0992
* Rougelsum: 30.1879
* Gen Len: 19.0


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: 8
* eval\_batch\_size: 24
* seed: 1799
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10


### Training results



### Framework versions


* Transformers 4.18.0
* Pytorch 1.10.0+cu111
* Datasets 2.5.1
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 8
* eval\_batch\_size: 24
* seed: 1799
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10 ### Training results ### Framework versions


* Transformers 4.18.0
* Pytorch 1.10.0+cu111
* 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: 8
* eval\_batch\_size: 24
* seed: 1799
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10 ### Training results ### Framework versions


* Transformers 4.18.0
* Pytorch 1.10.0+cu111
* 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: 8
* eval\_batch\_size: 24
* seed: 1799
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10### Training results### Framework versions


* Transformers 4.18.0
* Pytorch 1.10.0+cu111
* Datasets 2.5.1
* Tokenizers 0.12.1