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# mbart-large-50-clara-med

This model is a fine-tuned version of [facebook/mbart-large-50](https://huggingface.co/facebook/mbart-large-50) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 3.2121
- Rouge1: 49.1001
- Rouge2: 31.2516
- Rougel: 44.0446
- Rougelsum: 44.1075

## 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: 5.6e-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: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
| No log        | 1.0   | 190  | 1.8633          | 44.8593 | 28.0451 | 40.7724 | 40.8654   |
| No log        | 2.0   | 380  | 1.6667          | 46.8654 | 29.5857 | 42.6056 | 42.7844   |
| 3.317         | 3.0   | 570  | 1.6847          | 48.1605 | 30.163  | 43.1965 | 43.3317   |
| 3.317         | 4.0   | 760  | 1.7845          | 48.7615 | 30.8887 | 43.6946 | 43.8016   |
| 0.7441        | 5.0   | 950  | 2.0090          | 48.4207 | 30.64   | 43.654  | 43.7979   |
| 0.7441        | 6.0   | 1140 | 2.2425          | 49.1967 | 31.2644 | 44.0566 | 44.2112   |
| 0.7441        | 7.0   | 1330 | 2.4520          | 47.0568 | 28.7501 | 41.8219 | 41.9605   |
| 0.2396        | 8.0   | 1520 | 2.5336          | 47.969  | 30.0618 | 42.9924 | 43.1481   |
| 0.2396        | 9.0   | 1710 | 2.6153          | 47.2037 | 28.9732 | 42.0939 | 42.2242   |
| 0.1112        | 10.0  | 1900 | 2.7299          | 48.3657 | 30.3342 | 43.2025 | 43.3223   |
| 0.1112        | 11.0  | 2090 | 2.7696          | 48.0929 | 30.0156 | 42.9385 | 43.026    |
| 0.1112        | 12.0  | 2280 | 2.8627          | 48.1979 | 30.2714 | 43.0959 | 43.2027   |
| 0.0938        | 13.0  | 2470 | 2.8788          | 47.7685 | 29.5733 | 42.7561 | 42.9112   |
| 0.0938        | 14.0  | 2660 | 2.9128          | 47.5374 | 29.8217 | 42.7097 | 42.7803   |
| 0.0394        | 15.0  | 2850 | 2.9470          | 48.6385 | 30.1425 | 43.3326 | 43.3963   |
| 0.0394        | 16.0  | 3040 | 3.0039          | 48.6657 | 30.6642 | 43.471  | 43.592    |
| 0.0394        | 17.0  | 3230 | 3.0380          | 48.2351 | 30.5653 | 43.257  | 43.3788   |
| 0.023         | 18.0  | 3420 | 3.0289          | 48.6593 | 30.6916 | 43.7861 | 43.9098   |
| 0.023         | 19.0  | 3610 | 3.0733          | 49.2114 | 31.2737 | 44.0852 | 44.1993   |
| 0.0122        | 20.0  | 3800 | 3.1089          | 48.5431 | 30.5305 | 43.4128 | 43.5288   |
| 0.0122        | 21.0  | 3990 | 3.0684          | 48.4197 | 30.4005 | 43.2305 | 43.3214   |
| 0.0122        | 22.0  | 4180 | 3.1252          | 48.6007 | 30.5594 | 43.4008 | 43.5336   |
| 0.0071        | 23.0  | 4370 | 3.1572          | 48.7297 | 30.7028 | 43.436  | 43.5106   |
| 0.0071        | 24.0  | 4560 | 3.1716          | 48.9335 | 30.9918 | 43.7764 | 43.8044   |
| 0.0041        | 25.0  | 4750 | 3.1687          | 48.8731 | 31.1055 | 43.8021 | 43.8987   |
| 0.0041        | 26.0  | 4940 | 3.1845          | 48.9432 | 31.0766 | 43.8628 | 43.9726   |
| 0.0041        | 27.0  | 5130 | 3.2133          | 49.2016 | 31.1265 | 44.052  | 44.1427   |
| 0.0025        | 28.0  | 5320 | 3.2146          | 49.1473 | 31.3109 | 44.0372 | 44.1189   |
| 0.0025        | 29.0  | 5510 | 3.2121          | 49.2815 | 31.4258 | 44.1661 | 44.2436   |
| 0.0019        | 30.0  | 5700 | 3.2121          | 49.1001 | 31.2516 | 44.0446 | 44.1075   |


### Framework versions

- Transformers 4.25.1
- Pytorch 1.13.0
- Datasets 2.8.0
- Tokenizers 0.12.1

{"license": "mit", "tags": ["simplification", "generated_from_trainer"], "metrics": ["rouge"], "model-index": [{"name": "mbart-large-50-clara-med", "results": []}]}
transformers pytorch tensorboard mbart text2text-generation simplification generated_from_trainer license:mit autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #mbart #text2text-generation #simplification #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #region-us 

mbart-large-50-clara-med
========================


This model is a fine-tuned version of facebook/mbart-large-50 on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 3.2121
* Rouge1: 49.1001
* Rouge2: 31.2516
* Rougel: 44.0446
* Rougelsum: 44.1075


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: 5.6e-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: 30


### Training results



### Framework versions


* Transformers 4.25.1
* Pytorch 1.13.0
* Datasets 2.8.0
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5.6e-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: 30 ### Training results ### Framework versions


* Transformers 4.25.1
* Pytorch 1.13.0
* Datasets 2.8.0
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #mbart #text2text-generation #simplification #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5.6e-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: 30 ### Training results ### Framework versions


* Transformers 4.25.1
* Pytorch 1.13.0
* Datasets 2.8.0
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #mbart #text2text-generation #simplification #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5.6e-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: 30### Training results### Framework versions


* Transformers 4.25.1
* Pytorch 1.13.0
* Datasets 2.8.0
* Tokenizers 0.12.1