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# flan-t5-large-extraction-all-dm_4000-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: 1.5811
- Hint Hit Num: 2.366
- Hint Precision: 0.4373
- Num: 5.3574
- Gen Len: 18.7764

## 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: 12
- eval_batch_size: 96
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:------------:|:--------------:|:------:|:-------:|
| 2.2334        | 0.6   | 200  | 1.5968          | 2.7154       | 0.4867         | 5.6214 | 18.96   |
| 2.0104        | 1.2   | 400  | 1.5582          | 2.6402       | 0.4732         | 5.5972 | 18.9258 |
| 1.8919        | 1.8   | 600  | 1.5531          | 2.5878       | 0.4689         | 5.5198 | 18.8178 |
| 1.8495        | 2.4   | 800  | 1.5572          | 2.4834       | 0.4556         | 5.4372 | 18.8354 |
| 1.7984        | 2.99  | 1000 | 1.5569          | 2.426        | 0.4514         | 5.352  | 18.791  |
| 1.7446        | 3.59  | 1200 | 1.5443          | 2.4482       | 0.4502         | 5.4084 | 18.8278 |
| 1.7167        | 4.19  | 1400 | 1.5532          | 2.4502       | 0.4524         | 5.3864 | 18.8066 |
| 1.6838        | 4.79  | 1600 | 1.5603          | 2.3258       | 0.4387         | 5.2672 | 18.7164 |
| 1.6713        | 5.39  | 1800 | 1.5602          | 2.3874       | 0.4431         | 5.3434 | 18.7818 |
| 1.6403        | 5.99  | 2000 | 1.5636          | 2.313        | 0.4315         | 5.3092 | 18.7958 |
| 1.5963        | 6.59  | 2200 | 1.5745          | 2.353        | 0.4389         | 5.3184 | 18.7622 |
| 1.6203        | 7.19  | 2400 | 1.5757          | 2.3634       | 0.4348         | 5.3772 | 18.784  |
| 1.5808        | 7.78  | 2600 | 1.5822          | 2.33         | 0.4318         | 5.3452 | 18.8062 |
| 1.5436        | 8.38  | 2800 | 1.5791          | 2.3764       | 0.4394         | 5.3548 | 18.7792 |
| 1.5707        | 8.98  | 3000 | 1.5786          | 2.3592       | 0.4349         | 5.37   | 18.807  |
| 1.5512        | 9.58  | 3200 | 1.5820          | 2.362        | 0.4378         | 5.3418 | 18.773  |


### 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-dm_4000-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-dm\_4000-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: 1.5811
* Hint Hit Num: 2.366
* Hint Precision: 0.4373
* Num: 5.3574
* Gen Len: 18.7764


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: 12
* eval\_batch\_size: 96
* 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: 12
* eval\_batch\_size: 96
* 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: 12
* eval\_batch\_size: 96
* 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: 12
* eval\_batch\_size: 96
* 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