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# flan-t5-base-extraction-cnndm_20000-all-hint_precision-ep50

This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6865
- Hint Hit Num: 2.3572
- Hint Precision: 0.4273
- Num: 5.5014
- Gen Len: 18.9996

## 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: 60
- eval_batch_size: 400
- seed: 1799
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss | Hint Hit Num | Hint Precision | Num    | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------------:|:--------------:|:------:|:-------:|
| 2.1368        | 1.2   | 400  | 1.7751          | 2.203        | 0.4143         | 5.3192 | 18.9994 |
| 1.9563        | 2.4   | 800  | 1.7394          | 2.2359       | 0.4182         | 5.3459 | 18.9999 |
| 1.8966        | 3.59  | 1200 | 1.7167          | 2.2493       | 0.4172         | 5.3808 | 19.0    |
| 1.8669        | 4.79  | 1600 | 1.6975          | 2.2785       | 0.4208         | 5.4041 | 18.9999 |
| 1.8311        | 5.99  | 2000 | 1.6944          | 2.2849       | 0.4202         | 5.4243 | 18.9999 |
| 1.8044        | 7.19  | 2400 | 1.6918          | 2.2822       | 0.4214         | 5.4014 | 18.9998 |
| 1.7837        | 8.38  | 2800 | 1.6875          | 2.3155       | 0.425          | 5.4314 | 18.9999 |
| 1.7622        | 9.58  | 3200 | 1.6832          | 2.3069       | 0.423          | 5.4366 | 18.9996 |
| 1.7424        | 10.78 | 3600 | 1.6861          | 2.3173       | 0.4246         | 5.4455 | 18.9999 |
| 1.7318        | 11.98 | 4000 | 1.6856          | 2.3389       | 0.4246         | 5.4939 | 18.9999 |
| 1.7084        | 13.17 | 4400 | 1.6865          | 2.3572       | 0.4273         | 5.5014 | 18.9996 |
| 1.6946        | 14.37 | 4800 | 1.6817          | 2.3177       | 0.4219         | 5.4749 | 18.9996 |
| 1.685         | 15.57 | 5200 | 1.6884          | 2.3499       | 0.4262         | 5.4982 | 18.9999 |
| 1.6686        | 16.77 | 5600 | 1.6879          | 2.3466       | 0.4242         | 5.5094 | 18.9995 |
| 1.6583        | 17.96 | 6000 | 1.6885          | 2.3547       | 0.4255         | 5.5123 | 18.9993 |
| 1.6462        | 19.16 | 6400 | 1.6874          | 2.3582       | 0.4259         | 5.5165 | 18.9993 |


### 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"], "model-index": [{"name": "flan-t5-base-extraction-cnndm_20000-all-hint_precision-ep50", "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-base-extraction-cnndm\_20000-all-hint\_precision-ep50
=============================================================


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


* Loss: 1.6865
* Hint Hit Num: 2.3572
* Hint Precision: 0.4273
* Num: 5.5014
* Gen Len: 18.9996


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: 60
* eval\_batch\_size: 400
* seed: 1799
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 50


### 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: 60
* eval\_batch\_size: 400
* seed: 1799
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 50 ### 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: 60
* eval\_batch\_size: 400
* seed: 1799
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 50 ### 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: 60
* eval\_batch\_size: 400
* seed: 1799
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 50### Training results### Framework versions


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