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# mbart-large-50-pluska-token-sum

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: 4.2944
- Rouge1: 16.8143
- Rouge2: 5.2102
- Rougel: 14.3454
- Rougelsum: 14.7355

## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2 | Rougel  | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|
| No log        | 1.0   | 144  | 3.7149          | 17.1082 | 5.3773 | 14.6384 | 14.9023   |
| No log        | 2.0   | 288  | 3.4301          | 17.6442 | 5.7235 | 14.9728 | 15.3384   |
| No log        | 3.0   | 432  | 3.4951          | 17.491  | 5.5463 | 14.8284 | 15.2035   |
| 2.9135        | 4.0   | 576  | 3.6706          | 17.1471 | 5.3419 | 14.6302 | 14.9667   |
| 2.9135        | 5.0   | 720  | 3.9122          | 16.6979 | 5.1895 | 14.2909 | 14.6367   |
| 2.9135        | 6.0   | 864  | 4.0815          | 16.5961 | 5.1915 | 14.2459 | 14.5916   |
| 2.9135        | 7.0   | 1008 | 4.2448          | 16.7793 | 5.2088 | 14.3515 | 14.7136   |
| 1.0097        | 8.0   | 1152 | 4.2944          | 16.8143 | 5.2102 | 14.3454 | 14.7355   |


### Framework versions

- Transformers 4.27.0
- Pytorch 2.0.0
- Datasets 2.10.1
- Tokenizers 0.13.2

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

mbart-large-50-pluska-token-sum
===============================


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: 4.2944
* Rouge1: 16.8143
* Rouge2: 5.2102
* Rougel: 14.3454
* Rougelsum: 14.7355


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: 8
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 4
* total\_train\_batch\_size: 32
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 8


### Training results



### Framework versions


* Transformers 4.27.0
* Pytorch 2.0.0
* Datasets 2.10.1
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5.6e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 4
* total\_train\_batch\_size: 32
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 8 ### Training results ### Framework versions


* Transformers 4.27.0
* Pytorch 2.0.0
* Datasets 2.10.1
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #mbart #text2text-generation #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: 8
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 4
* total\_train\_batch\_size: 32
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 8 ### Training results ### Framework versions


* Transformers 4.27.0
* Pytorch 2.0.0
* Datasets 2.10.1
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #mbart #text2text-generation #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: 8
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 4
* total\_train\_batch\_size: 32
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 8### Training results### Framework versions


* Transformers 4.27.0
* Pytorch 2.0.0
* Datasets 2.10.1
* Tokenizers 0.13.2