metadata
license: apache-2.0
base_model: distilgpt2
tags:
- generated_from_trainer
datasets:
- generator
model-index:
- name: WO_CausalModel_2x
results: []
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
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 1.0 | 151 | 0.6217 |
| No log | 2.0 | 302 | 0.6133 |
| No log | 3.0 | 453 | 0.6087 |
| 0.6243 | 4.0 | 604 | 0.6079 |
| 0.6243 | 5.0 | 755 | 0.6049 |
| 0.6243 | 6.0 | 906 | 0.6035 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2