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# flan-t5-large-extraction-all-cnn_2000-ep10-nonstop

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: 1.7514
- Hint Hit Num: 1.973
- Hint Precision: 0.3391
- Num: 5.818
- Gen Len: 18.995

## 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: 128
- 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 | Hint Hit Num | Hint Precision | Num   | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------------:|:--------------:|:-----:|:-------:|
| 2.2357        | 0.8   | 100  | 1.8147          | 1.81         | 0.3173         | 5.756 | 18.997  |
| 1.9511        | 1.6   | 200  | 1.7767          | 1.961        | 0.3392         | 5.803 | 18.993  |
| 1.8506        | 2.4   | 300  | 1.7798          | 1.834        | 0.3218         | 5.712 | 18.993  |
| 1.7954        | 3.2   | 400  | 1.7513          | 1.899        | 0.3322         | 5.722 | 18.995  |
| 1.7482        | 4.0   | 500  | 1.7512          | 1.948        | 0.3373         | 5.794 | 18.995  |
| 1.7069        | 4.8   | 600  | 1.7475          | 1.936        | 0.3334         | 5.799 | 18.995  |
| 1.6723        | 5.6   | 700  | 1.7407          | 1.922        | 0.3355         | 5.752 | 18.995  |
| 1.6374        | 6.4   | 800  | 1.7492          | 1.941        | 0.3356         | 5.79  | 18.995  |
| 1.6437        | 7.2   | 900  | 1.7478          | 1.936        | 0.3364         | 5.758 | 18.995  |
| 1.6001        | 8.0   | 1000 | 1.7504          | 1.949        | 0.3363         | 5.784 | 18.995  |
| 1.5906        | 8.8   | 1100 | 1.7513          | 1.93         | 0.3335         | 5.784 | 18.995  |
| 1.5832        | 9.6   | 1200 | 1.7523          | 1.977        | 0.3396         | 5.823 | 18.995  |


### 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-large-extraction-all-cnn_2000-ep10-nonstop", "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-all-cnn\_2000-ep10-nonstop
===================================================


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: 1.7514
* Hint Hit Num: 1.973
* Hint Precision: 0.3391
* Num: 5.818
* Gen Len: 18.995


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: 128
* 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: 16
* eval\_batch\_size: 128
* 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: 16
* eval\_batch\_size: 128
* 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: 16
* eval\_batch\_size: 128
* 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