WO_CausalModel_2x

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WO_CausalModel_2x

This model is a fine-tuned version of distilgpt2 on the generator dataset. It achieves the following results on the evaluation set:

• Loss: 0.6035

Model description

It is focused on generating realistic WO descriptions when prompted with a given WO's priority, activity type, maintenance type, and location.

Intended uses & limitations

This is a proof of concept model for a larger project.

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 2e-05
• train_batch_size: 16
• eval_batch_size: 16
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 6

Training results

Framework versions

• Transformers 4.35.2
• Pytorch 2.1.0+cu121
• Datasets 2.17.1
• Tokenizers 0.15.2