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# bart-large-cnn-samsum-icsi-ami-v2

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: 5.8987
- Rouge1: 39.0928
- Rouge2: 10.8408
- Rougel: 21.9138
- Rougelsum: 35.5067
- Gen Len: 138.7941

## 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: 5e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len  |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:--------:|
| No log        | 1.0   | 135  | 3.2308          | 38.4274 | 13.6461 | 22.366  | 35.2353   | 185.7941 |
| No log        | 2.0   | 270  | 3.3026          | 40.1748 | 11.7944 | 23.2655 | 36.4718   | 146.8529 |
| No log        | 3.0   | 405  | 3.5199          | 39.8209 | 12.1621 | 22.7772 | 36.4967   | 141.7647 |
| 2.2131        | 4.0   | 540  | 4.0508          | 40.4325 | 11.6547 | 22.9958 | 36.8782   | 131.4412 |
| 2.2131        | 5.0   | 675  | 4.6988          | 38.4097 | 9.8309  | 20.3894 | 34.1967   | 145.9706 |
| 2.2131        | 6.0   | 810  | 4.9590          | 38.5758 | 9.6335  | 20.865  | 35.0321   | 169.2353 |
| 2.2131        | 7.0   | 945  | 5.4264          | 38.2813 | 9.5764  | 21.1406 | 34.5989   | 148.0294 |
| 0.401         | 8.0   | 1080 | 5.4887          | 38.3014 | 9.6881  | 21.2398 | 34.1584   | 139.3529 |
| 0.401         | 9.0   | 1215 | 5.8044          | 39.9603 | 10.4329 | 22.6895 | 36.2406   | 145.2353 |
| 0.401         | 10.0  | 1350 | 5.8987          | 39.0928 | 10.8408 | 21.9138 | 35.5067   | 138.7941 |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1+cu117
- Datasets 2.10.1
- Tokenizers 0.13.2

{"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["rouge"], "model-index": [{"name": "bart-large-cnn-samsum-icsi-ami-v2", "results": []}]}
transformers pytorch tensorboard bart text2text-generation generated_from_trainer license:mit autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #bart #text2text-generation #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #region-us 

bart-large-cnn-samsum-icsi-ami-v2
=================================


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: 5.8987
* Rouge1: 39.0928
* Rouge2: 10.8408
* Rougel: 21.9138
* Rougelsum: 35.5067
* Gen Len: 138.7941


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: 5e-05
* train\_batch\_size: 1
* eval\_batch\_size: 1
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10


### Training results



### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu117
* Datasets 2.10.1
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 1
* eval\_batch\_size: 1
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10 ### Training results ### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu117
* Datasets 2.10.1
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #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: 5e-05
* train\_batch\_size: 1
* eval\_batch\_size: 1
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10 ### Training results ### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu117
* Datasets 2.10.1
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #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: 5e-05
* train\_batch\_size: 1
* eval\_batch\_size: 1
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10### Training results### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu117
* Datasets 2.10.1
* Tokenizers 0.13.2