todos_task_model

This model is a fine-tuned version of distilbert-base-uncased on the vagrawal787/todo_task_list_types dataset. It achieves the following results on the evaluation set:

  • eval_loss: 0.2696
  • eval_accuracy: 0.95
  • eval_runtime: 0.2417
  • eval_samples_per_second: 248.265
  • eval_steps_per_second: 62.066
  • step: 0

Model description

Input: Text string of a todo-like task such as "get groceries" Output: A type label for what type of task it is (home, personal, work, emergency, etc.)

Intended uses & limitations

More information needed

Training and evaluation data

The dataset used is provided in the card.

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 2e-05
  • train_batch_size: 4
  • eval_batch_size: 4
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 4

Framework versions

  • Transformers 4.31.0
  • Pytorch 2.0.1+cu118
  • Datasets 2.14.1
  • Tokenizers 0.13.3
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Dataset used to train vagrawal787/todos_task_model