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# bart-large-cnn-samsum-ElectrifAi_v12

This model is a fine-tuned version of [philschmid/bart-large-cnn-samsum](https://huggingface.co/philschmid/bart-large-cnn-samsum) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.9357
- Rouge1: 52.8096
- Rouge2: 30.6135
- Rougel: 40.9225
- Rougelsum: 48.0235
- Gen Len: 80.6

## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| No log        | 1.0   | 11   | 2.1692          | 50.8653 | 25.2603 | 37.6053 | 46.5156   | 86.0    |
| No log        | 2.0   | 22   | 1.9852          | 49.1764 | 25.9935 | 38.3519 | 44.5786   | 75.4    |
| No log        | 3.0   | 33   | 1.9357          | 52.8096 | 30.6135 | 40.9225 | 48.0235   | 80.6    |


### Framework versions

- Transformers 4.25.1
- Pytorch 1.13.1+cu117
- Datasets 2.8.0
- Tokenizers 0.13.2

{"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["rouge"], "model-index": [{"name": "bart-large-cnn-samsum-ElectrifAi_v12", "results": []}]}
transformers pytorch bart text2text-generation generated_from_trainer license:mit autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #bart #text2text-generation #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #region-us 

bart-large-cnn-samsum-ElectrifAi\_v12
=====================================


This model is a fine-tuned version of philschmid/bart-large-cnn-samsum on an unknown dataset.
It achieves the following results on the evaluation set:


* Loss: 1.9357
* Rouge1: 52.8096
* Rouge2: 30.6135
* Rougel: 40.9225
* Rougelsum: 48.0235
* Gen Len: 80.6


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: 4
* eval\_batch\_size: 4
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 3
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.25.1
* Pytorch 1.13.1+cu117
* Datasets 2.8.0
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 4
* eval\_batch\_size: 4
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 3
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.25.1
* Pytorch 1.13.1+cu117
* Datasets 2.8.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #bart #text2text-generation #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 4
* eval\_batch\_size: 4
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 3
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.25.1
* Pytorch 1.13.1+cu117
* Datasets 2.8.0
* Tokenizers 0.13.2