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# flan-t5-base-extraction-cnndm_8000-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: 1.7529
- Hint Hit Num: 2.3661
- Hint Precision: 0.432
- Num: 5.4575
- Gen Len: 18.9999

## 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: 32
- eval_batch_size: 100
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:------------:|:--------------:|:------:|:-------:|
| 2.3309        | 0.8   | 200  | 1.8686          | 2.2144       | 0.415          | 5.3428 | 18.9925 |
| 2.0891        | 1.6   | 400  | 1.8016          | 2.2762       | 0.4225         | 5.3918 | 18.999  |
| 2.021         | 2.4   | 600  | 1.7832          | 2.2796       | 0.4222         | 5.3946 | 18.9994 |
| 1.9813        | 3.2   | 800  | 1.7706          | 2.319        | 0.4271         | 5.4208 | 18.9998 |
| 1.9465        | 4.0   | 1000 | 1.7521          | 2.327        | 0.4267         | 5.4423 | 18.9999 |
| 1.9139        | 4.8   | 1200 | 1.7491          | 2.3122       | 0.4255         | 5.412  | 18.9993 |
| 1.8886        | 5.6   | 1400 | 1.7506          | 2.3072       | 0.426          | 5.3995 | 18.9998 |
| 1.8753        | 6.4   | 1600 | 1.7529          | 2.3661       | 0.432          | 5.4575 | 18.9999 |
| 1.8432        | 7.2   | 1800 | 1.7428          | 2.3228       | 0.4249         | 5.4502 | 18.9998 |
| 1.8294        | 8.0   | 2000 | 1.7465          | 2.3463       | 0.4293         | 5.4482 | 18.9996 |
| 1.8072        | 8.8   | 2200 | 1.7403          | 2.3396       | 0.4271         | 5.4617 | 18.9993 |
| 1.7819        | 9.6   | 2400 | 1.7429          | 2.3223       | 0.4244         | 5.4575 | 18.9996 |
| 1.7732        | 10.4  | 2600 | 1.7446          | 2.3258       | 0.4254         | 5.4462 | 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-base-extraction-cnndm_8000-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\_8000-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: 1.7529
* Hint Hit Num: 2.3661
* Hint Precision: 0.432
* Num: 5.4575
* Gen Len: 18.9999


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: 32
* eval\_batch\_size: 100
* 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: 32
* eval\_batch\_size: 100
* 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: 32
* eval\_batch\_size: 100
* 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: 32
* eval\_batch\_size: 100
* 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