metadata
license: apache-2.0
base_model: google-bert/bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: bert_intent
results: []
bert_intent
This model is a fine-tuned version of google-bert/bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0184
- Accuracy: 0.9975
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: 1e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.3247 | 1.0 | 693 | 0.0407 | 0.9895 |
| 0.024 | 2.0 | 1386 | 0.0220 | 0.9951 |
| 0.0076 | 3.0 | 2079 | 0.0144 | 0.9958 |
| 0.0048 | 4.0 | 2772 | 0.0111 | 0.9965 |
| 0.0031 | 5.0 | 3465 | 0.0076 | 0.9975 |
| 0.0014 | 6.0 | 4158 | 0.0069 | 0.9979 |
| 0.0009 | 7.0 | 4851 | 0.0073 | 0.9972 |
| 0.0005 | 8.0 | 5544 | 0.0071 | 0.9972 |
| 0.0003 | 9.0 | 6237 | 0.0074 | 0.9972 |
| 0.0002 | 10.0 | 6930 | 0.0073 | 0.9975 |
| 0.0001 | 11.0 | 7623 | 0.0077 | 0.9972 |
| 0.0001 | 12.0 | 8316 | 0.0078 | 0.9972 |
| 0.0001 | 13.0 | 9009 | 0.0082 | 0.9972 |
| 0.0001 | 14.0 | 9702 | 0.0086 | 0.9972 |
| 0.0 | 15.0 | 10395 | 0.0087 | 0.9975 |
| 0.0 | 16.0 | 11088 | 0.0088 | 0.9975 |
| 0.0 | 17.0 | 11781 | 0.0092 | 0.9975 |
| 0.0 | 18.0 | 12474 | 0.0101 | 0.9975 |
| 0.0 | 19.0 | 13167 | 0.0107 | 0.9975 |
| 0.0 | 20.0 | 13860 | 0.0117 | 0.9972 |
| 0.0 | 21.0 | 14553 | 0.0114 | 0.9975 |
| 0.0 | 22.0 | 15246 | 0.0121 | 0.9975 |
| 0.0 | 23.0 | 15939 | 0.0127 | 0.9972 |
| 0.0 | 24.0 | 16632 | 0.0128 | 0.9975 |
| 0.0 | 25.0 | 17325 | 0.0133 | 0.9972 |
| 0.0 | 26.0 | 18018 | 0.0140 | 0.9975 |
| 0.0 | 27.0 | 18711 | 0.0140 | 0.9975 |
| 0.0 | 28.0 | 19404 | 0.0145 | 0.9972 |
| 0.0 | 29.0 | 20097 | 0.0145 | 0.9972 |
| 0.0 | 30.0 | 20790 | 0.0150 | 0.9975 |
| 0.0 | 31.0 | 21483 | 0.0150 | 0.9975 |
| 0.0 | 32.0 | 22176 | 0.0158 | 0.9972 |
| 0.0 | 33.0 | 22869 | 0.0160 | 0.9972 |
| 0.0 | 34.0 | 23562 | 0.0166 | 0.9972 |
| 0.0 | 35.0 | 24255 | 0.0165 | 0.9972 |
| 0.0 | 36.0 | 24948 | 0.0169 | 0.9972 |
| 0.0 | 37.0 | 25641 | 0.0170 | 0.9975 |
| 0.0 | 38.0 | 26334 | 0.0172 | 0.9975 |
| 0.0 | 39.0 | 27027 | 0.0175 | 0.9975 |
| 0.0 | 40.0 | 27720 | 0.0175 | 0.9975 |
| 0.0 | 41.0 | 28413 | 0.0177 | 0.9975 |
| 0.0 | 42.0 | 29106 | 0.0179 | 0.9975 |
| 0.0 | 43.0 | 29799 | 0.0180 | 0.9975 |
| 0.0 | 44.0 | 30492 | 0.0181 | 0.9975 |
| 0.0 | 45.0 | 31185 | 0.0182 | 0.9975 |
| 0.0 | 46.0 | 31878 | 0.0183 | 0.9975 |
| 0.0 | 47.0 | 32571 | 0.0183 | 0.9975 |
| 0.0 | 48.0 | 33264 | 0.0183 | 0.9975 |
| 0.0 | 49.0 | 33957 | 0.0183 | 0.9975 |
| 0.0 | 50.0 | 34650 | 0.0184 | 0.9975 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.1
- Datasets 2.19.2
- Tokenizers 0.19.1