
# led-base-16384-text_summarization_data

This model is a fine-tuned version of [allenai/led-base-16384](https://huggingface.co/allenai/led-base-16384) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9531
- Rouge1: 43.3689
- Rouge2: 19.9885
- RougeL: 39.9887
- RougeLsum: 40.0679
- Gen Len: 14.0392

## Model description

This is a text summarization model.

For more information on how it was created, check out the following link: https://github.com/DunnBC22/NLP_Projects/blob/main/Text%20Summarization/Text-Summarized%20Data%20-%20Comparison/LED%20-%20Text%20Summarization%20-%204%20Epochs.ipynb

## Intended uses & limitations

This model is intended to demonstrate my ability to solve a complex problem using technology.

## Training and evaluation data

Dataset Source: https://www.kaggle.com/datasets/cuitengfeui/textsummarization-data

## 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: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | RougeL  | RougeLsum | General Length |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 1.329         | 1.0   | 1197 | 0.9704          | 42.4111 | 19.8995 | 39.4717 | 39.5449   | 14.254  |
| 0.8367        | 2.0   | 2394 | 0.9425          | 43.1141 | 19.6089 | 39.7533 | 39.8298   | 14.1058 |
| 0.735         | 3.0   | 3591 | 0.9421          | 42.8101 | 19.8281 | 39.617  | 39.6751   | 13.7101 |
| 0.6737        | 4.0   | 4788 | 0.9531          | 43.3689 | 19.9885 | 39.9887 | 40.0679   | 14.0392 |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.12.1
- Datasets 2.9.0
- Tokenizers 0.12.1
{"language": ["en"], "license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["rouge"], "pipeline_tag": "summarization", "model-index": [{"name": "led-base-16384-text_summarization_data", "results": []}]}
transformers pytorch tensorboard led text2text-generation generated_from_trainer summarization en license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #led #text2text-generation #generated_from_trainer #summarization #en #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 

led-base-16384-text\_summarization\_data
========================================


This model is a fine-tuned version of allenai/led-base-16384 on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 0.9531
* Rouge1: 43.3689
* Rouge2: 19.9885
* RougeL: 39.9887
* RougeLsum: 40.0679
* Gen Len: 14.0392


Model description
-----------------


This is a text summarization model.


For more information on how it was created, check out the following link: URL


Intended uses & limitations
---------------------------


This model is intended to demonstrate my ability to solve a complex problem using technology.


Training and evaluation data
----------------------------


Dataset Source: URL


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: 4


### Training results



### Framework versions


* Transformers 4.26.1
* Pytorch 1.12.1
* Datasets 2.9.0
* Tokenizers 0.12.1



### 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: 4 ### Training results ### Framework versions


* Transformers 4.26.1
* Pytorch 1.12.1
* Datasets 2.9.0
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #led #text2text-generation #generated_from_trainer #summarization #en #license-apache-2.0 #autotrain_compatible #endpoints_compatible #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: 4 ### Training results ### Framework versions


* Transformers 4.26.1
* Pytorch 1.12.1
* Datasets 2.9.0
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #led #text2text-generation #generated_from_trainer #summarization #en #license-apache-2.0 #autotrain_compatible #endpoints_compatible #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: 4### Training results### Framework versions


* Transformers 4.26.1
* Pytorch 1.12.1
* Datasets 2.9.0
* Tokenizers 0.12.1