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# flan-t5-large-extraction-cnndm_20000-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: 1.6652
- Rouge1: 35.487
- Rouge2: 15.6713
- Rougel: 29.9519
- Rougelsum: 29.9368
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 2.1295        | 0.08  | 200  | 1.8266          | 34.0465 | 14.7511 | 29.3395 | 29.3437   | 19.0    |
| 1.9354        | 0.16  | 400  | 1.7732          | 34.7923 | 15.3094 | 29.8484 | 29.8757   | 18.99   |
| 1.854         | 0.24  | 600  | 1.7367          | 34.8358 | 15.1969 | 29.9971 | 30.0064   | 18.986  |
| 1.833         | 0.32  | 800  | 1.7120          | 34.7854 | 15.5144 | 29.8141 | 29.7863   | 18.982  |
| 1.8217        | 0.4   | 1000 | 1.7256          | 34.7274 | 15.2763 | 30.0298 | 30.0871   | 19.0    |
| 1.8309        | 0.48  | 1200 | 1.7089          | 35.4328 | 15.7724 | 30.0655 | 30.0199   | 19.0    |
| 1.825         | 0.56  | 1400 | 1.6947          | 35.4116 | 15.6911 | 30.1438 | 30.1764   | 19.0    |
| 1.7914        | 0.64  | 1600 | 1.7119          | 35.5918 | 16.3762 | 30.3234 | 30.2807   | 19.0    |
| 1.7889        | 0.72  | 1800 | 1.6810          | 35.6413 | 15.8936 | 30.2848 | 30.2291   | 19.0    |
| 1.7576        | 0.8   | 2000 | 1.6826          | 35.9424 | 15.6803 | 30.5998 | 30.5571   | 19.0    |
| 1.7763        | 0.88  | 2200 | 1.6748          | 35.7543 | 15.984  | 30.7197 | 30.721    | 18.998  |
| 1.7604        | 0.96  | 2400 | 1.6652          | 35.487  | 15.6713 | 29.9519 | 29.9368   | 19.0    |
| 1.7138        | 1.04  | 2600 | 1.6860          | 36.0333 | 16.4065 | 30.7249 | 30.7168   | 19.0    |
| 1.6951        | 1.12  | 2800 | 1.6792          | 35.3149 | 15.7178 | 30.1555 | 30.1517   | 18.998  |
| 1.6752        | 1.2   | 3000 | 1.6832          | 34.7566 | 15.4179 | 29.7687 | 29.8259   | 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_20000-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\_20000-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: 1.6652
* Rouge1: 35.487
* Rouge2: 15.6713
* Rougel: 29.9519
* Rougelsum: 29.9368
* 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