bert-tiny-finetuned-wnut17-ner
This model is a fine-tuned version of google/bert_uncased_L-2_H-128_A-2 on the wnut_17 dataset. It achieves the following results on the evaluation set:
- Loss: 0.6054
- Precision: 0.0
- Recall: 0.0
- F1: 0.0
- Accuracy: 0.8961
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: 128
- eval_batch_size: 128
- 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 |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 27 | 1.1060 | 0.0 | 0.0 | 0.0 | 0.8961 |
| No log | 2.0 | 54 | 0.9075 | 0.0 | 0.0 | 0.0 | 0.8961 |
| No log | 3.0 | 81 | 0.7978 | 0.0 | 0.0 | 0.0 | 0.8961 |
| No log | 4.0 | 108 | 0.7333 | 0.0 | 0.0 | 0.0 | 0.8961 |
| No log | 5.0 | 135 | 0.6929 | 0.0 | 0.0 | 0.0 | 0.8961 |
| No log | 6.0 | 162 | 0.6661 | 0.0 | 0.0 | 0.0 | 0.8961 |
| No log | 7.0 | 189 | 0.6477 | 0.0 | 0.0 | 0.0 | 0.8961 |
| No log | 8.0 | 216 | 0.6346 | 0.0 | 0.0 | 0.0 | 0.8961 |
| No log | 9.0 | 243 | 0.6251 | 0.0 | 0.0 | 0.0 | 0.8961 |
| No log | 10.0 | 270 | 0.6182 | 0.0 | 0.0 | 0.0 | 0.8961 |
| No log | 11.0 | 297 | 0.6132 | 0.0 | 0.0 | 0.0 | 0.8961 |
| No log | 12.0 | 324 | 0.6097 | 0.0 | 0.0 | 0.0 | 0.8961 |
| No log | 13.0 | 351 | 0.6073 | 0.0 | 0.0 | 0.0 | 0.8961 |
| No log | 14.0 | 378 | 0.6059 | 0.0 | 0.0 | 0.0 | 0.8961 |
| No log | 15.0 | 405 | 0.6054 | 0.0 | 0.0 | 0.0 | 0.8961 |
Framework versions
- Transformers 4.21.0
- Pytorch 1.12.0+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1