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

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: 1.6853
- Rouge1: 34.5211
- Rouge2: 15.298
- Rougel: 29.4229
- Rougelsum: 29.5024
- 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: 16
- eval_batch_size: 48
- seed: 1799
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 2.1308        | 0.4   | 200  | 1.7871          | 34.3185 | 14.8966 | 29.6706 | 29.7468   | 19.0    |
| 1.9291        | 0.8   | 400  | 1.7315          | 34.4255 | 15.1159 | 29.5114 | 29.609    | 18.99   |
| 1.8624        | 1.2   | 600  | 1.7356          | 35.4244 | 15.3865 | 30.0524 | 30.0961   | 18.99   |
| 1.8106        | 1.6   | 800  | 1.7151          | 34.8718 | 15.5046 | 29.9394 | 30.0119   | 19.0    |
| 1.7948        | 2.0   | 1000 | 1.7103          | 33.8176 | 14.974  | 29.3676 | 29.4451   | 18.99   |
| 1.7303        | 2.4   | 1200 | 1.6940          | 34.8851 | 15.4393 | 30.1554 | 30.2106   | 19.0    |
| 1.7276        | 2.8   | 1400 | 1.6853          | 34.5211 | 15.298  | 29.4229 | 29.5024   | 19.0    |
| 1.6804        | 3.2   | 1600 | 1.7031          | 35.0279 | 15.7442 | 29.9333 | 30.0312   | 19.0    |
| 1.6597        | 3.6   | 1800 | 1.6939          | 35.4139 | 15.9005 | 30.1214 | 30.1721   | 18.998  |
| 1.6432        | 4.0   | 2000 | 1.6874          | 34.8249 | 15.4814 | 29.794  | 29.8873   | 18.998  |
| 1.5921        | 4.4   | 2200 | 1.6940          | 34.7792 | 15.5349 | 29.6781 | 29.7601   | 19.0    |
| 1.6044        | 4.8   | 2400 | 1.6956          | 35.7927 | 16.1867 | 30.6689 | 30.7588   | 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-new", "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-new
============================================


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: 1.6853
* Rouge1: 34.5211
* Rouge2: 15.298
* Rougel: 29.4229
* Rougelsum: 29.5024
* 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: 16
* eval\_batch\_size: 48
* seed: 1799
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 20


### 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: 16
* eval\_batch\_size: 48
* seed: 1799
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 20 ### 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: 16
* eval\_batch\_size: 48
* seed: 1799
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 20 ### 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: 16
* eval\_batch\_size: 48
* seed: 1799
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 20### Training results### Framework versions


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