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# IndicBART-ibart-hi-to-en

This model is a fine-tuned version of [ai4bharat/IndicBART](https://huggingface.co/ai4bharat/IndicBART) on the hindi_english_machine_translation dataset.

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

### Training results

| Training Loss | Epoch | Step | Validation Loss | Bleu   | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|
| No log        | 1.0   | 157  | 4.4208          | 1.0626 | 20.0    |


### Framework versions

- Transformers 4.19.1
- Pytorch 1.11.0+cu102
- Datasets 1.18.0
- Tokenizers 0.12.1

{"tags": ["generated_from_trainer"], "datasets": ["hindi_english_machine_translation"], "model-index": [{"name": "IndicBART-ibart-hi-to-en", "results": []}]}
transformers pytorch tensorboard mbart text2text-generation generated_from_trainer dataset:hindi_english_machine_translation autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #mbart #text2text-generation #generated_from_trainer #dataset-hindi_english_machine_translation #autotrain_compatible #endpoints_compatible #region-us 

IndicBART-ibart-hi-to-en
========================


This model is a fine-tuned version of ai4bharat/IndicBART on the hindi\_english\_machine\_translation dataset.


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


### Training results



### Framework versions


* Transformers 4.19.1
* Pytorch 1.11.0+cu102
* Datasets 1.18.0
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 32
* eval\_batch\_size: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 1 ### Training results ### Framework versions


* Transformers 4.19.1
* Pytorch 1.11.0+cu102
* Datasets 1.18.0
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #mbart #text2text-generation #generated_from_trainer #dataset-hindi_english_machine_translation #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 32
* eval\_batch\_size: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 1 ### Training results ### Framework versions


* Transformers 4.19.1
* Pytorch 1.11.0+cu102
* Datasets 1.18.0
* Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #tensorboard #mbart #text2text-generation #generated_from_trainer #dataset-hindi_english_machine_translation #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 32
* eval\_batch\_size: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 1### Training results### Framework versions


* Transformers 4.19.1
* Pytorch 1.11.0+cu102
* Datasets 1.18.0
* Tokenizers 0.12.1