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# output

This model is a fine-tuned version of [google/mt5-base](https://huggingface.co/google/mt5-base) on dataset [x-tech/cantonese-mandarin-translations](https://huggingface.co/datasets/x-tech/cantonese-mandarin-translations).

## Model description

The model translates Cantonese sentences to Mandarin.

## Intended uses & limitations

When you use the model, please make sure to add `translate cantonese to mandarin: <sentence>` (please note the space after colon) before the text you want to translate.

## Training and evaluation data

Training Dataset: [x-tech/cantonese-mandarin-translations](https://huggingface.co/datasets/x-tech/cantonese-mandarin-translations)
## Training procedure

Training is based on [example in transformers library](https://github.com/huggingface/transformers/tree/master/examples/pytorch/translation)

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 1
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0

### Training results

Since we still need to set up validation set, we do not have any training results yet.

### Framework versions

- Transformers 4.12.5
- Pytorch 1.8.1
- Datasets 1.15.1
- Tokenizers 0.10.3

{"language": ["yue", "zh", "multilingual"], "license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["botisan-ai/cantonese-mandarin-translations"], "base_model": "google/mt5-base", "model-index": [{"name": "output", "results": []}]}
transformers pytorch safetensors mt5 text2text-generation generated_from_trainer yue zh multilingual dataset:botisan-ai/cantonese-mandarin-translations base_model:google/mt5-base license:apache-2.0 autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #safetensors #mt5 #text2text-generation #generated_from_trainer #yue #zh #multilingual #dataset-botisan-ai/cantonese-mandarin-translations #base_model-google/mt5-base #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 




# output

This model is a fine-tuned version of google/mt5-base on dataset x-tech/cantonese-mandarin-translations.

## Model description

The model translates Cantonese sentences to Mandarin.

## Intended uses & limitations

When you use the model, please make sure to add 'translate cantonese to mandarin: <sentence>' (please note the space after colon) before the text you want to translate.

## Training and evaluation data

Training Dataset: x-tech/cantonese-mandarin-translations
## Training procedure

Training is based on example in transformers library

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 1
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0

### Training results

Since we still need to set up validation set, we do not have any training results yet.

### Framework versions

- Transformers 4.12.5
- Pytorch 1.8.1
- Datasets 1.15.1
- Tokenizers 0.10.3

# output

This model is a fine-tuned version of google/mt5-base on dataset x-tech/cantonese-mandarin-translations. ## Model description

The model translates Cantonese sentences to Mandarin. ## Intended uses & limitations

When you use the model, please make sure to add 'translate cantonese to mandarin: <sentence>' (please note the space after colon) before the text you want to translate. ## Training and evaluation data

Training Dataset: x-tech/cantonese-mandarin-translations ## Training procedure

Training is based on example in transformers library ### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 1
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0 ### Training results

Since we still need to set up validation set, we do not have any training results yet. ### Framework versions

- Transformers 4.12.5
- Pytorch 1.8.1
- Datasets 1.15.1
- Tokenizers 0.10.3
TAGS
#transformers #pytorch #safetensors #mt5 #text2text-generation #generated_from_trainer #yue #zh #multilingual #dataset-botisan-ai/cantonese-mandarin-translations #base_model-google/mt5-base #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
 # output

This model is a fine-tuned version of google/mt5-base on dataset x-tech/cantonese-mandarin-translations. ## Model description

The model translates Cantonese sentences to Mandarin. ## Intended uses & limitations

When you use the model, please make sure to add 'translate cantonese to mandarin: <sentence>' (please note the space after colon) before the text you want to translate. ## Training and evaluation data

Training Dataset: x-tech/cantonese-mandarin-translations ## Training procedure

Training is based on example in transformers library ### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 1
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0 ### Training results

Since we still need to set up validation set, we do not have any training results yet. ### Framework versions

- Transformers 4.12.5
- Pytorch 1.8.1
- Datasets 1.15.1
- Tokenizers 0.10.3
passage: TAGS
#transformers #pytorch #safetensors #mt5 #text2text-generation #generated_from_trainer #yue #zh #multilingual #dataset-botisan-ai/cantonese-mandarin-translations #base_model-google/mt5-base #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
# output

This model is a fine-tuned version of google/mt5-base on dataset x-tech/cantonese-mandarin-translations.## Model description

The model translates Cantonese sentences to Mandarin.## Intended uses & limitations

When you use the model, please make sure to add 'translate cantonese to mandarin: <sentence>' (please note the space after colon) before the text you want to translate.## Training and evaluation data

Training Dataset: x-tech/cantonese-mandarin-translations## Training procedure

Training is based on example in transformers library### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 1
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0### Training results

Since we still need to set up validation set, we do not have any training results yet.### Framework versions

- Transformers 4.12.5
- Pytorch 1.8.1
- Datasets 1.15.1
- Tokenizers 0.10.3