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# bart-base-finetuned-en-to-ro

This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co/facebook/bart-base) on the wmt16 dataset.
It achieves the following results on the evaluation set:
- Loss: 1.9912

## 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: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: IPU
- gradient_accumulation_steps: 128
- total_train_batch_size: 512
- total_eval_batch_size: 24
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
- training precision: Mixed Precision

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.5409        | 1.0   | 1192 | 1.9912          |


### Framework versions

- Transformers 4.21.1
- Pytorch 1.10.0+cpu
- Datasets 2.4.0
- Tokenizers 0.12.1

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["wmt16"], "model-index": [{"name": "bart-base-finetuned-en-to-ro", "results": []}]}
transformers pytorch optimum_graphcore bart text2text-generation generated_from_trainer dataset:wmt16 license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #optimum_graphcore #bart #text2text-generation #generated_from_trainer #dataset-wmt16 #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 

bart-base-finetuned-en-to-ro
============================


This model is a fine-tuned version of facebook/bart-base on the wmt16 dataset.
It achieves the following results on the evaluation set:


* Loss: 1.9912


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: 1
* eval\_batch\_size: 1
* seed: 42
* distributed\_type: IPU
* gradient\_accumulation\_steps: 128
* total\_train\_batch\_size: 512
* total\_eval\_batch\_size: 24
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 1
* training precision: Mixed Precision


### Training results



### Framework versions


* Transformers 4.21.1
* Pytorch 1.10.0+cpu
* Datasets 2.4.0
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 1
* eval\_batch\_size: 1
* seed: 42
* distributed\_type: IPU
* gradient\_accumulation\_steps: 128
* total\_train\_batch\_size: 512
* total\_eval\_batch\_size: 24
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 1
* training precision: Mixed Precision ### Training results ### Framework versions


* Transformers 4.21.1
* Pytorch 1.10.0+cpu
* Datasets 2.4.0
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #optimum_graphcore #bart #text2text-generation #generated_from_trainer #dataset-wmt16 #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 1
* eval\_batch\_size: 1
* seed: 42
* distributed\_type: IPU
* gradient\_accumulation\_steps: 128
* total\_train\_batch\_size: 512
* total\_eval\_batch\_size: 24
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 1
* training precision: Mixed Precision ### Training results ### Framework versions


* Transformers 4.21.1
* Pytorch 1.10.0+cpu
* Datasets 2.4.0
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #optimum_graphcore #bart #text2text-generation #generated_from_trainer #dataset-wmt16 #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 1
* eval\_batch\_size: 1
* seed: 42
* distributed\_type: IPU
* gradient\_accumulation\_steps: 128
* total\_train\_batch\_size: 512
* total\_eval\_batch\_size: 24
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 1
* training precision: Mixed Precision### Training results### Framework versions


* Transformers 4.21.1
* Pytorch 1.10.0+cpu
* Datasets 2.4.0
* Tokenizers 0.12.1