---
license: mit
language:
- en
metrics:
- accuracy
library_name: adapter-transformers
tags:
- code
Here is a sample model card for the project:
Model Card: Multitask Learning for Agent-Action Identification
Model Name: Agent-Action Identifier
Model Type: Multitask Learning Model
Model Description:
The Agent-Action Identifier is a multitask learning model that identifies agents and actions in text data. The model is trained on a custom dataset of text examples, where each example is annotated with the agents and actions present in the text.
Model Architecture:
Encoder: BERT (bert-base-uncased)
Classification Heads: Two classification heads for agents and actions
Model Parameters: 120M parameters
Training Data:
Dataset: Custom dataset of text examples
Training Set: 10,000 examples
Validation Set: 1,250 examples
Testing Set: 1,250 examples
Training Hyperparameters:
Batch Size: 16
Number of Epochs: 3
Learning Rate: 1e-5
Optimizer: AdamW
Evaluation Metrics:
Accuracy: 92.5% on validation set
F1-Score: 91.2% on validation set
Intended Use:
The Agent-Action Identifier is intended for use in natural language processing applications, such as text analysis and information extraction.
Limitations:
Dataset bias: The model is trained on a custom dataset and may not generalize well to other datasets.
Overfitting: The model may overfit to the training data, especially if the training set is small.
Ethics:
Data privacy: The dataset used to train the model is anonymized and does not contain any personally identifiable information.
Bias and fairness: The model is designed to be fair and unbiased, but may still reflect biases present in the training data.
Model Performance:
Accuracy: 92.5% on validation set
F1-Score: 91.2% on validation set
Precision: 93.1% on validation set
Recall: 91.5% on validation set
How to Use:
Input: Text data
Output: Identified agents and actions
Code: Python code using the Hugging Face Transformers library
Citation:
If you use the Agent-Action Identifier in your research, please cite the following paper:
[Insert paper citation]
License:
The Agent-Action Identifier is licensed under the MIT License.
Contact:
For more information, please contact [dduncan@ddroidlabs.com].
I hope this sample model card meets your requirements! Let me know if you have any further requests.
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