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# flan-t5-base-extraction-cnndm_2000-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: 1.8809
- Hint Hit Num: 2.3633
- Hint Precision: 0.4277
- Num: 5.5061
- Gen Len: 18.9963

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:------------:|:--------------:|:------:|:-------:|
| 2.2998        | 3.17  | 200  | 1.8793          | 2.1611       | 0.41           | 5.2739 | 18.9821 |
| 2.005         | 6.35  | 400  | 1.8404          | 2.2977       | 0.4239         | 5.4206 | 18.9834 |
| 1.9122        | 9.52  | 600  | 1.8202          | 2.2932       | 0.4219         | 5.4262 | 18.9984 |
| 1.8362        | 12.7  | 800  | 1.8211          | 2.3419       | 0.4265         | 5.4797 | 18.9977 |
| 1.7743        | 15.87 | 1000 | 1.8206          | 2.3377       | 0.4256         | 5.4791 | 18.9975 |
| 1.722         | 19.05 | 1200 | 1.8310          | 2.3149       | 0.4242         | 5.4426 | 18.9983 |
| 1.6762        | 22.22 | 1400 | 1.8378          | 2.3138       | 0.4219         | 5.4592 | 18.9981 |
| 1.6396        | 25.4  | 1600 | 1.8457          | 2.3373       | 0.4261         | 5.4672 | 18.9975 |
| 1.6067        | 28.57 | 1800 | 1.8501          | 2.3552       | 0.4272         | 5.4914 | 18.9969 |
| 1.579         | 31.75 | 2000 | 1.8561          | 2.3567       | 0.4273         | 5.4933 | 18.9983 |
| 1.5516        | 34.92 | 2200 | 1.8662          | 2.3504       | 0.4262         | 5.4943 | 18.998  |
| 1.5368        | 38.1  | 2400 | 1.8755          | 2.3547       | 0.4264         | 5.4993 | 18.9966 |
| 1.5155        | 41.27 | 2600 | 1.8809          | 2.3633       | 0.4277         | 5.5061 | 18.9963 |
| 1.5123        | 44.44 | 2800 | 1.8801          | 2.3665       | 0.4271         | 5.5183 | 18.9972 |
| 1.5007        | 47.62 | 3000 | 1.8840          | 2.3535       | 0.4253         | 5.5096 | 18.9969 |


### 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_2000-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\_2000-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: 1.8809
* Hint Hit Num: 2.3633
* Hint Precision: 0.4277
* Num: 5.5061
* Gen Len: 18.9963


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