metadata
language:
- en
license: apache-2.0
tags:
- t5-small
- text2text-generation
- natural language understanding
- conversational system
- task-oriented dialog
datasets:
- ConvLab/tm2
metrics:
- Dialog acts Accuracy
- Dialog acts F1
model-index:
- name: t5-small-nlu-tm2-context3
results:
- task:
type: text2text-generation
name: natural language understanding
dataset:
type: ConvLab/tm2
name: Taskmaster-2
split: test
revision: cdc314b156e7f7ffa81a1e7398f1f8a2e86c0095
metrics:
- type: Dialog acts Accuracy
value: 82.4
name: Accuracy
- type: Dialog acts F1
value: 74.3
name: F1
widget:
- text: >-
user: Hi, I'm looking for a flight. I need to visit a friend.
system: Hello, how can I help you? Sure, I can help you with that. On what
dates?
user: I'm looking to travel from March 20th to 22nd.
- text: |-
system: Anything else?
user: That should be everything.
system: I found a flight for $424 on United Airlines.
user: Okay, is that for New York?
inference:
parameters:
max_length: 100
t5-small-nlu-tm2-context3
This model is a fine-tuned version of t5-small on Taskmaster-2 with context window size == 3.
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: 128
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 256
- optimizer: Adafactor
- lr_scheduler_type: linear
- num_epochs: 10.0
Framework versions
- Transformers 4.18.0
- Pytorch 1.10.2+cu102
- Datasets 1.18.3
- Tokenizers 0.11.0