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# flan-t5-base-extraction-cnndm_4000-all-loss-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: 1.7725
- Hint Hit Num: 2.3971
- Hint Precision: 0.4325
- Num: 5.5242
- Gen Len: 18.9994

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:------------:|:--------------:|:------:|:-------:|
| 2.4364        | 1.49  | 100  | 1.9011          | 2.2142       | 0.4104         | 5.4023 | 18.9832 |
| 2.1323        | 2.99  | 200  | 1.8601          | 2.2703       | 0.4207         | 5.4015 | 18.9909 |
| 2.053         | 4.48  | 300  | 1.8248          | 2.3204       | 0.4264         | 5.4393 | 18.996  |
| 1.9901        | 5.97  | 400  | 1.8057          | 2.3274       | 0.4276         | 5.434  | 18.9989 |
| 1.9581        | 7.46  | 500  | 1.7883          | 2.3746       | 0.4323         | 5.4853 | 18.9992 |
| 1.924         | 8.96  | 600  | 1.7860          | 2.3598       | 0.4305         | 5.4683 | 18.9996 |
| 1.8916        | 10.45 | 700  | 1.7822          | 2.3769       | 0.4316         | 5.4918 | 18.9998 |
| 1.8678        | 11.94 | 800  | 1.7885          | 2.3537       | 0.43           | 5.457  | 18.999  |
| 1.8388        | 13.43 | 900  | 1.7785          | 2.3959       | 0.4335         | 5.5158 | 18.9987 |
| 1.8219        | 14.93 | 1000 | 1.7790          | 2.3789       | 0.4309         | 5.5044 | 18.9987 |
| 1.8016        | 16.42 | 1100 | 1.7789          | 2.3677       | 0.4306         | 5.485  | 18.9991 |
| 1.7739        | 17.91 | 1200 | 1.7725          | 2.3971       | 0.4325         | 5.5242 | 18.9994 |
| 1.7626        | 19.4  | 1300 | 1.7852          | 2.3603       | 0.4289         | 5.483  | 18.9991 |
| 1.7512        | 20.9  | 1400 | 1.7821          | 2.3861       | 0.4314         | 5.5117 | 18.9993 |
| 1.7319        | 22.39 | 1500 | 1.7821          | 2.3966       | 0.4323         | 5.5287 | 18.9994 |
| 1.7135        | 23.88 | 1600 | 1.7893          | 2.403        | 0.433          | 5.5313 | 18.9993 |
| 1.7004        | 25.37 | 1700 | 1.7853          | 2.4254       | 0.4345         | 5.5673 | 18.9996 |


### 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_4000-all-loss-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\_4000-all-loss-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: 1.7725
* Hint Hit Num: 2.3971
* Hint Precision: 0.4325
* Num: 5.5242
* Gen Len: 18.9994


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