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# summarizing_literature

This model is a fine-tuned version of [psin/my_awesome_billsum_model](https://huggingface.co/psin/my_awesome_billsum_model) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 3.3867
- Rouge1: 0.105
- Rouge2: 0.015
- Rougel: 0.0858
- Rougelsum: 0.086
- Gen Len: 19.0

## 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: 72
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| No log        | 1.0   | 19   | 3.5487          | 0.0994 | 0.0127 | 0.0816 | 0.0813    | 19.0    |
| No log        | 2.0   | 38   | 3.4905          | 0.1007 | 0.0137 | 0.0825 | 0.0823    | 19.0    |
| No log        | 3.0   | 57   | 3.4557          | 0.1006 | 0.0138 | 0.0832 | 0.0832    | 19.0    |
| No log        | 4.0   | 76   | 3.4327          | 0.0994 | 0.014  | 0.081  | 0.0809    | 19.0    |
| No log        | 5.0   | 95   | 3.4168          | 0.0992 | 0.0142 | 0.0817 | 0.0816    | 19.0    |
| No log        | 6.0   | 114  | 3.4049          | 0.0992 | 0.0127 | 0.0816 | 0.0818    | 19.0    |
| No log        | 7.0   | 133  | 3.3965          | 0.1024 | 0.0142 | 0.0838 | 0.0839    | 19.0    |
| No log        | 8.0   | 152  | 3.3909          | 0.1049 | 0.0156 | 0.086  | 0.0862    | 19.0    |
| No log        | 9.0   | 171  | 3.3878          | 0.1052 | 0.0156 | 0.0864 | 0.0865    | 19.0    |
| No log        | 10.0  | 190  | 3.3867          | 0.105  | 0.015  | 0.0858 | 0.086     | 19.0    |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["rouge"], "model-index": [{"name": "summarizing_literature", "results": []}]}
transformers pytorch tensorboard t5 text2text-generation generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #tensorboard #t5 #text2text-generation #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

summarizing\_literature
=======================


This model is a fine-tuned version of psin/my\_awesome\_billsum\_model on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 3.3867
* Rouge1: 0.105
* Rouge2: 0.015
* Rougel: 0.0858
* Rougelsum: 0.086
* Gen Len: 19.0


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: 72
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 72
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #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: 16
* seed: 72
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3