<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. -->
BACnet-Klassifizierung-Kaeltettechnik-bert-base-german-cased
This model is a fine-tuned version of bert-base-german-cased on the gart-labor "klassifizierung_kaelte_v2" dataset. It achieves the following results on the evaluation set:
- Loss: 0.0466
- F1: [0.85714286 0.98507463 1. 1. ]
Model description
This model makes it possible to classify the refrigeration components described with the BACnet standard into different categories. The model is based on a German-language data set.
Intended uses & limitations
The model divides descriptive texts into the following refrigeration categories: Free_Cooling, Refrigeration_General, Chiller, Cold Storage and Recooling Plant
Training and evaluation data
The model is based on a German-language data set.
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8.0
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|---|---|---|---|---|
| 0.0426 | 0.85 | 5 | 0.0439 | [0.85714286 0.98507463 1. 1. ] |
| 0.0175 | 1.85 | 10 | 0.0466 | [0.85714286 0.98507463 1. 1. ] |
Framework versions
- Transformers 4.21.1
- Pytorch 1.12.0+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1
