metadata
library_name: transformers
license: apache-2.0
base_model: google-bert/bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: bert-text-classifier
results: []
bert-text-classifier
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: 0.2881
- Accuracy: 0.867
- Auc: 0.952
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: 0.0002
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Auc |
|---|---|---|---|---|---|
| 0.5028 | 1.0 | 263 | 0.3810 | 0.818 | 0.913 |
| 0.4105 | 2.0 | 526 | 0.3386 | 0.838 | 0.931 |
| 0.3571 | 3.0 | 789 | 0.3130 | 0.853 | 0.94 |
| 0.3556 | 4.0 | 1052 | 0.3417 | 0.853 | 0.946 |
| 0.3539 | 5.0 | 1315 | 0.3438 | 0.86 | 0.948 |
| 0.3473 | 6.0 | 1578 | 0.2908 | 0.869 | 0.95 |
| 0.3341 | 7.0 | 1841 | 0.2865 | 0.878 | 0.95 |
| 0.3106 | 8.0 | 2104 | 0.2884 | 0.867 | 0.95 |
| 0.3131 | 9.0 | 2367 | 0.2833 | 0.873 | 0.952 |
| 0.3143 | 10.0 | 2630 | 0.2881 | 0.867 | 0.952 |
Framework versions
- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.5.1
- Tokenizers 0.21.1