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# bart-large-finetuned-bart

This model is a fine-tuned version of [facebook/bart-large](https://huggingface.co/facebook/bart-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8644
- Rouge1: 80.883
- Rouge2: 72.0268
- Rougel: 77.0146
- Rougelsum: 77.3408
- Gen Len: 19.2969

## 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: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| No log        | 1.0   | 12   | 0.8158          | 70.5188 | 55.0313 | 61.668  | 62.0697   | 18.8281 |
| No log        | 2.0   | 24   | 0.6610          | 78.9718 | 67.9238 | 71.2508 | 71.5416   | 19.2188 |
| No log        | 3.0   | 36   | 0.6257          | 79.2603 | 69.4298 | 73.031  | 73.4136   | 19.1875 |
| No log        | 4.0   | 48   | 0.6354          | 79.0425 | 69.7772 | 73.6893 | 73.8356   | 19.3125 |
| No log        | 5.0   | 60   | 0.6126          | 79.9003 | 69.6148 | 73.3622 | 73.7154   | 19.2656 |
| No log        | 6.0   | 72   | 0.6537          | 80.0209 | 69.9125 | 73.6876 | 73.9664   | 19.1875 |
| No log        | 7.0   | 84   | 0.7168          | 80.7559 | 71.8251 | 75.5574 | 75.6627   | 19.2031 |
| No log        | 8.0   | 96   | 0.6980          | 80.9116 | 72.2951 | 75.9015 | 76.2205   | 19.2656 |
| No log        | 9.0   | 108  | 0.7569          | 80.1034 | 70.8352 | 75.1723 | 75.4102   | 19.25   |
| No log        | 10.0  | 120  | 0.7523          | 80.0436 | 71.0855 | 75.8337 | 76.1002   | 19.3281 |
| No log        | 11.0  | 132  | 0.7742          | 80.5982 | 71.713  | 75.9081 | 76.1564   | 19.4375 |
| No log        | 12.0  | 144  | 0.7570          | 79.4243 | 70.5775 | 75.3521 | 75.9334   | 19.4844 |
| No log        | 13.0  | 156  | 0.8225          | 80.2529 | 72.6598 | 76.6931 | 76.8326   | 19.7344 |
| No log        | 14.0  | 168  | 0.8696          | 79.821  | 71.2369 | 75.836  | 76.0734   | 19.4688 |
| No log        | 15.0  | 180  | 0.8820          | 80.9234 | 72.5022 | 76.7848 | 77.0368   | 19.375  |
| No log        | 16.0  | 192  | 0.8400          | 80.5926 | 72.0275 | 76.8664 | 77.0773   | 19.2969 |
| No log        | 17.0  | 204  | 0.8461          | 80.6004 | 72.2808 | 76.8693 | 77.0517   | 19.375  |
| No log        | 18.0  | 216  | 0.8577          | 81.0069 | 73.1954 | 77.467  | 77.7083   | 19.3906 |
| No log        | 19.0  | 228  | 0.8695          | 81.0333 | 72.5324 | 77.4248 | 77.5971   | 19.2969 |
| No log        | 20.0  | 240  | 0.8644          | 80.883  | 72.0268 | 77.0146 | 77.3408   | 19.2969 |


### 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": "bart-large-finetuned-bart", "results": []}]}
transformers pytorch tensorboard bart text2text-generation generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #bart #text2text-generation #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 

bart-large-finetuned-bart
=========================


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


* Loss: 0.8644
* Rouge1: 80.883
* Rouge2: 72.0268
* Rougel: 77.0146
* Rougelsum: 77.3408
* Gen Len: 19.2969


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: 20
* 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: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 20
* 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 #bart #text2text-generation #generated_from_trainer #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: 20
* 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 #bart #text2text-generation #generated_from_trainer #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: 20
* 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