<!-- 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. -->
electra-base-ner-food-recipe
This model is a fine-tuned version of google/electra-base-discriminator on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1889
- Precision: 0.7866
- Recall: 0.8144
- F1: 0.8003
- Accuracy: 0.9558
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-06
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.0216 | 2.66 | 2121 | 0.1672 | 0.7858 | 0.8183 | 0.8017 | 0.9575 |
| 0.0237 | 5.33 | 4242 | 0.1744 | 0.7842 | 0.8122 | 0.7980 | 0.9564 |
| 0.0281 | 7.99 | 6363 | 0.1793 | 0.7812 | 0.8148 | 0.7976 | 0.9558 |
| 0.0236 | 10.66 | 8484 | 0.1863 | 0.7923 | 0.8148 | 0.8034 | 0.9567 |
| 0.0246 | 13.32 | 10605 | 0.1881 | 0.7871 | 0.8170 | 0.8018 | 0.9561 |
Framework versions
- Transformers 4.27.4
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3
