
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# bart-samsum

This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co/facebook/bart-base) on the samsum dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5071
- Rouge1: 0.4835
- Rouge2: 0.2546
- Rougel: 0.4128
- Rougelsum: 0.4131
- Gen Len: 17.9817

## 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: 4
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 1.8082        | 1.0   | 2947  | 1.5613          | 0.4763 | 0.2412 | 0.4043 | 0.4041    | 17.9332 |
| 1.5609        | 2.0   | 5894  | 1.5206          | 0.4827 | 0.2485 | 0.4082 | 0.4085    | 18.3169 |
| 1.4228        | 3.0   | 8841  | 1.5008          | 0.4851 | 0.2557 | 0.4138 | 0.4137    | 17.9851 |
| 1.3131        | 4.0   | 11788 | 1.5071          | 0.4835 | 0.2546 | 0.4128 | 0.4131    | 17.9817 |


### 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"], "datasets": ["samsum"], "metrics": ["rouge"], "model-index": [{"name": "bart-samsum", "results": [{"task": {"type": "text2text-generation", "name": "Sequence-to-sequence Language Modeling"}, "dataset": {"name": "samsum", "type": "samsum", "config": "samsum", "split": "train", "args": "samsum"}, "metrics": [{"type": "rouge", "value": 0.4835, "name": "Rouge1"}]}]}]}
transformers pytorch tensorboard bart text2text-generation generated_from_trainer dataset:samsum license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #bart #text2text-generation #generated_from_trainer #dataset-samsum #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 

bart-samsum
===========


This model is a fine-tuned version of facebook/bart-base on the samsum dataset.
It achieves the following results on the evaluation set:


* Loss: 1.5071
* Rouge1: 0.4835
* Rouge2: 0.2546
* Rougel: 0.4128
* Rougelsum: 0.4131
* Gen Len: 17.9817


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: 4
* 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: 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: 4
* 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 #dataset-samsum #license-apache-2.0 #model-index #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: 4
* 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