
<!-- 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-large-extraction-cnndm_2000-all-ep10

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: 1.7621
- Rouge1: 34.9279
- Rouge2: 15.2498
- Rougel: 29.9179
- Rougelsum: 29.9082
- Gen Len: 18.986

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 2.1649        | 0.8   | 200  | 1.8161          | 34.9419 | 14.942  | 29.7831 | 29.8328   | 19.0    |
| 1.9114        | 1.6   | 400  | 1.7713          | 34.825  | 14.6572 | 29.7393 | 29.7646   | 18.986  |
| 1.7997        | 2.4   | 600  | 1.7917          | 34.1619 | 14.8104 | 29.6399 | 29.6155   | 18.99   |
| 1.7477        | 3.2   | 800  | 1.7771          | 35.0584 | 15.3149 | 29.9349 | 29.9183   | 18.99   |
| 1.6821        | 4.0   | 1000 | 1.7621          | 34.9279 | 15.2498 | 29.9179 | 29.9082   | 18.986  |
| 1.6301        | 4.8   | 1200 | 1.7796          | 34.3508 | 14.8522 | 29.5811 | 29.5785   | 18.99   |
| 1.597         | 5.6   | 1400 | 1.7669          | 35.3844 | 15.7633 | 30.4042 | 30.4473   | 18.99   |
| 1.5543        | 6.4   | 1600 | 1.7857          | 34.4823 | 15.0787 | 29.7926 | 29.7856   | 18.99   |
| 1.5473        | 7.2   | 1800 | 1.7854          | 34.7347 | 15.1301 | 29.8061 | 29.8492   | 18.99   |
| 1.5017        | 8.0   | 2000 | 1.7920          | 35.0512 | 15.2671 | 30.2014 | 30.2702   | 18.99   |
| 1.4874        | 8.8   | 2200 | 1.7978          | 35.1954 | 15.518  | 30.2292 | 30.2755   | 18.99   |
| 1.4798        | 9.6   | 2400 | 1.7938          | 35.1686 | 15.5524 | 30.3497 | 30.3741   | 18.99   |


### 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_2000-all-ep10", "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\_2000-all-ep10
=============================================


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: 1.7621
* Rouge1: 34.9279
* Rouge2: 15.2498
* Rougel: 29.9179
* Rougelsum: 29.9082
* Gen Len: 18.986


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