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# test-dialogue-summarization

This model is a fine-tuned version of [facebook/bart-large-xsum](https://huggingface.co/facebook/bart-large-xsum) on the samsum dataset.
It achieves the following results on the evaluation set:
- Loss: 1.7499
- Rouge1: 53.8085
- Rouge2: 28.9627
- Rougel: 44.3913
- Rougelsum: 49.5056
- Gen Len: 30.2237

## 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
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 1.3909        | 1.0   | 1841 | 1.5591          | 52.8029 | 28.5133 | 43.7896 | 48.3986   | 25.8386 |
| 1.0938        | 2.0   | 3683 | 1.4337          | 54.5987 | 29.195  | 44.2764 | 49.9201   | 31.9071 |
| 0.856         | 3.0   | 5524 | 1.5402          | 54.2077 | 29.0463 | 44.3965 | 49.6877   | 29.4597 |
| 0.6704        | 4.0   | 7366 | 1.6280          | 54.2616 | 29.5501 | 44.5626 | 49.7599   | 29.967  |
| 0.548         | 5.0   | 9205 | 1.7499          | 53.8085 | 28.9627 | 44.3913 | 49.5056   | 30.2237 |


### Framework versions

- Transformers 4.27.4
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3

{"license": "mit", "tags": ["generated_from_trainer"], "datasets": ["samsum"], "metrics": ["rouge"], "model-index": [{"name": "test-dialogue-summarization", "results": [{"task": {"type": "text2text-generation", "name": "Sequence-to-sequence Language Modeling"}, "dataset": {"name": "samsum", "type": "samsum", "config": "samsum", "split": "validation", "args": "samsum"}, "metrics": [{"type": "rouge", "value": 53.8085, "name": "Rouge1"}]}]}]}
transformers pytorch bart text2text-generation generated_from_trainer dataset:samsum license:mit model-index autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #bart #text2text-generation #generated_from_trainer #dataset-samsum #license-mit #model-index #autotrain_compatible #endpoints_compatible #region-us 

test-dialogue-summarization
===========================


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


* Loss: 1.7499
* Rouge1: 53.8085
* Rouge2: 28.9627
* Rougel: 44.3913
* Rougelsum: 49.5056
* Gen Len: 30.2237


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
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 8
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 5
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.27.4
* Pytorch 2.0.0+cu118
* Datasets 2.11.0
* 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
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 8
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 5
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.27.4
* Pytorch 2.0.0+cu118
* Datasets 2.11.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #bart #text2text-generation #generated_from_trainer #dataset-samsum #license-mit #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
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 8
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 5
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.27.4
* Pytorch 2.0.0+cu118
* Datasets 2.11.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #bart #text2text-generation #generated_from_trainer #dataset-samsum #license-mit #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
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 8
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 5
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.27.4
* Pytorch 2.0.0+cu118
* Datasets 2.11.0
* Tokenizers 0.13.3