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# Usage

Translates to Acholi, Lugbara, Luganda, Runyankole and Ateso

Make sure to add a target language and dataset tags before a source sentence.

Ex. >>lug_hq<< I want Posho ---> Njagala Posho

For biblical style translations attempt to use the ood tag

Ex. >>lug_ood<< And thus spoke the LORD to the masses on the mountain

We these other tags which you might want to try [ggl, bt, hq, ood]

Language tags [ach, lgg, lug, nyn, teo]


### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.0001
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 5000
- total_train_batch_size: 5000
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
- label_smoothing_factor: 0.1

### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Tokenizers 0.13.3

{"tags": ["generated_from_trainer"], "model-index": [{"name": "best", "results": []}]}
transformers pytorch marian text2text-generation generated_from_trainer autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #marian #text2text-generation #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 




# Usage

Translates to Acholi, Lugbara, Luganda, Runyankole and Ateso

Make sure to add a target language and dataset tags before a source sentence.

Ex. >>lug_hq<< I want Posho ---> Njagala Posho

For biblical style translations attempt to use the ood tag

Ex. >>lug_ood<< And thus spoke the LORD to the masses on the mountain

We these other tags which you might want to try [ggl, bt, hq, ood]

Language tags [ach, lgg, lug, nyn, teo]


### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.0001
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 5000
- total_train_batch_size: 5000
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
- label_smoothing_factor: 0.1

### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Tokenizers 0.13.3

# Usage

Translates to Acholi, Lugbara, Luganda, Runyankole and Ateso

Make sure to add a target language and dataset tags before a source sentence.

Ex. >>lug_hq<< I want Posho ---> Njagala Posho

For biblical style translations attempt to use the ood tag

Ex. >>lug_ood<< And thus spoke the LORD to the masses on the mountain

We these other tags which you might want to try [ggl, bt, hq, ood]

Language tags [ach, lgg, lug, nyn, teo] ### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.0001
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 5000
- total_train_batch_size: 5000
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
- label_smoothing_factor: 0.1 ### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Tokenizers 0.13.3
TAGS
#transformers #pytorch #marian #text2text-generation #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 
 # Usage

Translates to Acholi, Lugbara, Luganda, Runyankole and Ateso

Make sure to add a target language and dataset tags before a source sentence.

Ex. >>lug_hq<< I want Posho ---> Njagala Posho

For biblical style translations attempt to use the ood tag

Ex. >>lug_ood<< And thus spoke the LORD to the masses on the mountain

We these other tags which you might want to try [ggl, bt, hq, ood]

Language tags [ach, lgg, lug, nyn, teo] ### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.0001
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 5000
- total_train_batch_size: 5000
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
- label_smoothing_factor: 0.1 ### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Tokenizers 0.13.3
TAGS
#transformers #pytorch #marian #text2text-generation #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 
# Usage

Translates to Acholi, Lugbara, Luganda, Runyankole and Ateso

Make sure to add a target language and dataset tags before a source sentence.

Ex. >>lug_hq<< I want Posho ---> Njagala Posho

For biblical style translations attempt to use the ood tag

Ex. >>lug_ood<< And thus spoke the LORD to the masses on the mountain

We these other tags which you might want to try [ggl, bt, hq, ood]

Language tags [ach, lgg, lug, nyn, teo]### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.0001
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 5000
- total_train_batch_size: 5000
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
- label_smoothing_factor: 0.1### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Tokenizers 0.13.3