lm-ner-linkedin-skills-recognition
This model is a fine-tuned version of algiraldohe/distilbert-base-uncased-linkedin-domain-adaptation on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0307
- Precision: 0.9119
- Recall: 0.9312
- F1: 0.9214
- Accuracy: 0.9912
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-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.1301 | 1.0 | 729 | 0.0468 | 0.8786 | 0.8715 | 0.8750 | 0.9863 |
| 0.0432 | 2.0 | 1458 | 0.0345 | 0.8994 | 0.9219 | 0.9105 | 0.9900 |
| 0.0332 | 3.0 | 2187 | 0.0307 | 0.9119 | 0.9312 | 0.9214 | 0.9912 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3
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