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# flan-t5-large-extraction-all-cnn_2000-ep25-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: 1.8888
- Hint Hit Num: 2.01
- Hint Precision: 0.3447
- Num: 5.837
- Gen Len: 18.999

## 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: 64
- seed: 1799
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 25

### Training results

| Training Loss | Epoch | Step | Validation Loss | Hint Hit Num | Hint Precision | Num   | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------------:|:--------------:|:-----:|:-------:|
| 2.0904        | 1.6   | 200  | 1.7731          | 1.981        | 0.3417         | 5.823 | 18.993  |
| 1.8113        | 3.2   | 400  | 1.7548          | 1.927        | 0.3363         | 5.741 | 18.995  |
| 1.6986        | 4.8   | 600  | 1.7478          | 1.95         | 0.3349         | 5.825 | 18.995  |
| 1.6024        | 6.4   | 800  | 1.7592          | 1.925        | 0.3317         | 5.808 | 18.994  |
| 1.5406        | 8.0   | 1000 | 1.7628          | 1.97         | 0.339          | 5.815 | 18.995  |
| 1.4624        | 9.6   | 1200 | 1.7749          | 1.974        | 0.3378         | 5.839 | 18.988  |
| 1.4123        | 11.2  | 1400 | 1.7986          | 1.952        | 0.3355         | 5.82  | 18.995  |
| 1.3698        | 12.8  | 1600 | 1.8116          | 1.99         | 0.3413         | 5.841 | 18.999  |
| 1.3246        | 14.4  | 1800 | 1.8241          | 1.97         | 0.3368         | 5.842 | 18.999  |
| 1.2865        | 16.0  | 2000 | 1.8407          | 2.016        | 0.3467         | 5.827 | 18.999  |
| 1.2549        | 17.6  | 2200 | 1.8636          | 2.023        | 0.3427         | 5.905 | 18.999  |
| 1.2345        | 19.2  | 2400 | 1.8752          | 2.018        | 0.3439         | 5.874 | 18.999  |
| 1.2122        | 20.8  | 2600 | 1.8750          | 2.001        | 0.3438         | 5.827 | 18.999  |
| 1.2002        | 22.4  | 2800 | 1.8814          | 2.026        | 0.3461         | 5.868 | 18.999  |
| 1.1957        | 24.0  | 3000 | 1.8862          | 2.015        | 0.3457         | 5.832 | 18.999  |


### 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-ep25-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-ep25-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: 1.8888
* Hint Hit Num: 2.01
* Hint Precision: 0.3447
* Num: 5.837
* Gen Len: 18.999


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: 64
* seed: 1799
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 25


### 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: 64
* seed: 1799
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 25 ### 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: 64
* seed: 1799
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 25 ### 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: 64
* seed: 1799
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 25### Training results### Framework versions


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