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--- |
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license: apache-2.0 |
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base_model: distilgpt2 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- generator |
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model-index: |
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- name: WO_CausalModel_2x |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# WO_CausalModel_2x |
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This model is a fine-tuned version of [distilgpt2](https://huggingface.co/distilgpt2) on the generator dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6035 |
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## Model description |
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It is focused on generating realistic WO descriptions when prompted with a given WO's priority, activity type, maintenance type, and location. |
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## Intended uses & limitations |
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This is a proof of concept model for a larger project. |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 6 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| No log | 1.0 | 151 | 0.6217 | |
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| No log | 2.0 | 302 | 0.6133 | |
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| No log | 3.0 | 453 | 0.6087 | |
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| 0.6243 | 4.0 | 604 | 0.6079 | |
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| 0.6243 | 5.0 | 755 | 0.6049 | |
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| 0.6243 | 6.0 | 906 | 0.6035 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.17.1 |
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- Tokenizers 0.15.2 |
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