
# mt5-small-nlg-all-crosswoz

This model is a fine-tuned version of [mt5-small](https://huggingface.co/mt5-small) on [CrossWOZ](https://huggingface.co/datasets/ConvLab/crosswoz) both user and system utterances.

Refer to [ConvLab-3](https://github.com/ConvLab/ConvLab-3) for model description and usage.

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.001
- train_batch_size: 32
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 256
- optimizer: Adafactor
- lr_scheduler_type: linear
- num_epochs: 10.0

### Framework versions

- Transformers 4.20.1
- Pytorch 1.11.0+cu102
- Datasets 2.3.2
- Tokenizers 0.12.1
{"language": ["zh"], "license": "apache-2.0", "tags": ["mt5-small", "text2text-generation", "natural language generation", "conversational system", "task-oriented dialog"], "datasets": ["ConvLab/crosswoz"], "metrics": ["Slot Error Rate", "sacrebleu"], "widget": [{"text": "[Inform][\u9152\u5e97]([\u4ef7\u683c][100-200\u5143],[\u8bc4\u5206][5\u5206]);[greet][General]([][]);[Request][\u9152\u5e97]([\u540d\u79f0][])\n\nuser: "}, {"text": "[Recommend][\u9152\u5e97]([\u540d\u79f0][\u5317\u4eac\u4eac\u4eea\u5927\u9152\u5e97],[\u540d\u79f0][\u5317\u4eac\u8d35\u90fd\u5927\u9152\u5e97]);[Inform][\u9152\u5e97]([\u9152\u5e97\u8bbe\u65bd-\u5065\u8eab\u623f-\u5426][]);[NoOffer][\u9152\u5e97]([][])\n\nsystem: "}], "inference": {"parameters": {"max_length": 100}}, "model-index": [{"name": "mt5-small-nlg-all-crosswoz", "results": [{"task": {"type": "text2text-generation", "name": "natural language generation"}, "dataset": {"name": "CrossWOZ", "type": "ConvLab/crosswoz", "split": "test", "revision": "4a3e56082543ed9eecb9c76ef5eadc1aa0cc5ca0"}, "metrics": [{"type": "Slot Error Rate", "value": 6.9, "name": "SER"}, {"type": "sacrebleu", "value": 21.0, "name": "BLEU"}]}]}]}
transformers pytorch mt5 text2text-generation mt5-small natural language generation conversational system task-oriented dialog zh dataset:ConvLab/crosswoz license:apache-2.0 model-index autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #mt5 #text2text-generation #mt5-small #natural language generation #conversational system #task-oriented dialog #zh #dataset-ConvLab/crosswoz #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 


# mt5-small-nlg-all-crosswoz

This model is a fine-tuned version of mt5-small on CrossWOZ both user and system utterances.

Refer to ConvLab-3 for model description and usage.

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.001
- train_batch_size: 32
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 256
- optimizer: Adafactor
- lr_scheduler_type: linear
- num_epochs: 10.0

### Framework versions

- Transformers 4.20.1
- Pytorch 1.11.0+cu102
- Datasets 2.3.2
- Tokenizers 0.12.1
# mt5-small-nlg-all-crosswoz

This model is a fine-tuned version of mt5-small on CrossWOZ both user and system utterances.

Refer to ConvLab-3 for model description and usage. ## Training procedure ### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.001
- train_batch_size: 32
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 256
- optimizer: Adafactor
- lr_scheduler_type: linear
- num_epochs: 10.0 ### Framework versions

- Transformers 4.20.1
- Pytorch 1.11.0+cu102
- Datasets 2.3.2
- Tokenizers 0.12.1
TAGS
#transformers #pytorch #mt5 #text2text-generation #mt5-small #natural language generation #conversational system #task-oriented dialog #zh #dataset-ConvLab/crosswoz #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
 # mt5-small-nlg-all-crosswoz

This model is a fine-tuned version of mt5-small on CrossWOZ both user and system utterances.

Refer to ConvLab-3 for model description and usage. ## Training procedure ### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.001
- train_batch_size: 32
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 256
- optimizer: Adafactor
- lr_scheduler_type: linear
- num_epochs: 10.0 ### Framework versions

- Transformers 4.20.1
- Pytorch 1.11.0+cu102
- Datasets 2.3.2
- Tokenizers 0.12.1
TAGS
#transformers #pytorch #mt5 #text2text-generation #mt5-small #natural language generation #conversational system #task-oriented dialog #zh #dataset-ConvLab/crosswoz #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
# mt5-small-nlg-all-crosswoz

This model is a fine-tuned version of mt5-small on CrossWOZ both user and system utterances.

Refer to ConvLab-3 for model description and usage.## Training procedure### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.001
- train_batch_size: 32
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 256
- optimizer: Adafactor
- lr_scheduler_type: linear
- num_epochs: 10.0### Framework versions

- Transformers 4.20.1
- Pytorch 1.11.0+cu102
- Datasets 2.3.2
- Tokenizers 0.12.1