NER-BERT-10KData
This model is a fine-tuned version of bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4232
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: 0.0003
- 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
- training_steps: 1000
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
0.2951 | 2.3256 | 100 | 0.4395 |
0.1989 | 4.6512 | 200 | 0.4701 |
0.1302 | 6.9767 | 300 | 0.4402 |
0.0967 | 9.3023 | 400 | 0.4868 |
0.0603 | 11.6279 | 500 | 0.4259 |
0.0365 | 13.9535 | 600 | 0.4508 |
0.0168 | 16.2791 | 700 | 0.4267 |
0.0119 | 18.6047 | 800 | 0.4077 |
0.0054 | 20.9302 | 900 | 0.4196 |
0.0027 | 23.2558 | 1000 | 0.4232 |
Framework versions
- Transformers 4.44.0
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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Model tree for mehmetalpy/NER-BERT-10KData
Base model
google-bert/bert-base-uncased