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# gcicontracts

This model is a fine-tuned version of [mjbeattie/mjbbillsum](https://huggingface.co/mjbeattie/mjbbillsum) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.0721
- Rouge1: 0.2917
- Rouge2: 0.1209
- Rougel: 0.2556
- Rougelsum: 0.2535
- Gen Len: 18.1463

## 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: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| No log        | 1.0   | 11   | 2.4545          | 0.3004 | 0.1333 | 0.2658 | 0.2637    | 18.2927 |
| No log        | 2.0   | 22   | 2.3030          | 0.3047 | 0.1397 | 0.2744 | 0.2709    | 18.2927 |
| No log        | 3.0   | 33   | 2.2187          | 0.3065 | 0.1416 | 0.276  | 0.2718    | 18.2439 |
| No log        | 4.0   | 44   | 2.1562          | 0.2926 | 0.1209 | 0.2558 | 0.2538    | 18.2439 |
| No log        | 5.0   | 55   | 2.1172          | 0.2926 | 0.1209 | 0.2558 | 0.2538    | 18.2439 |
| No log        | 6.0   | 66   | 2.0921          | 0.2914 | 0.1209 | 0.2552 | 0.253     | 18.1463 |
| No log        | 7.0   | 77   | 2.0786          | 0.2917 | 0.1209 | 0.2556 | 0.2535    | 18.1463 |
| No log        | 8.0   | 88   | 2.0721          | 0.2917 | 0.1209 | 0.2556 | 0.2535    | 18.1463 |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1
- Datasets 2.10.0
- Tokenizers 0.11.0
{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["rouge"], "pipeline_tag": "summarization", "model-index": [{"name": "gcicontracts", "results": []}]}
transformers pytorch t5 text2text-generation generated_from_trainer summarization license:apache-2.0 autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #t5 #text2text-generation #generated_from_trainer #summarization #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

gcicontracts
============


This model is a fine-tuned version of mjbeattie/mjbbillsum on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 2.0721
* Rouge1: 0.2917
* Rouge2: 0.1209
* Rougel: 0.2556
* Rougelsum: 0.2535
* Gen Len: 18.1463


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: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 8
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1
* Datasets 2.10.0
* Tokenizers 0.11.0



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 8
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1
* Datasets 2.10.0
* Tokenizers 0.11.0
TAGS
#transformers #pytorch #t5 #text2text-generation #generated_from_trainer #summarization #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: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 8
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1
* Datasets 2.10.0
* Tokenizers 0.11.0
TAGS
#transformers #pytorch #t5 #text2text-generation #generated_from_trainer #summarization #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: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 8
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1
* Datasets 2.10.0
* Tokenizers 0.11.0